diff --git a/linear-regression(grade prediction).R b/R/linear-regression(grade prediction).R
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rename from linear-regression(grade prediction).R
rename to R/linear-regression(grade prediction).R
diff --git a/README.md b/README.md
index ba93e10..256bb8b 100644
--- a/README.md
+++ b/README.md
@@ -1,6 +1,53 @@
 # [Hacktober-Open](https://client69.github.io/Hacktober-Open/)
 ## You can add some good algorithms (in any language) which can be helpful for competitive programmers. <br> I will merge it with hacktoberfest-accepted label
 
+
+Welcome to **Open** — a community-driven collection of open source code, snippets, and small projects.  
+This repository is designed to help **new contributors** learn, practice, and share useful code across different languages.
+
+All contributions are welcome! 🚀
+
+---
+
+## 📌 How You Can Contribute
+1. Fork this repository.
+2. Add your script, project, or snippet in the appropriate folder.
+   - Example: add a Python script in `/python/`
+   - Or create a small project inside `/projects/`
+3. Update the README in your folder (if needed).
+4. Make a Pull Request (PR).
+
+---
+
+## 📂 Repository Structure
+- `python/` → Python programs  
+- `javascript/` → JavaScript programs  
+- `algorithms/` → Common algorithms in any language  
+- `projects/` → Small apps, CLI tools, or experiments  
+- `docs/` → Guides, notes, or tutorials  
+- `Rust/` →  Rust programs  
+- Or any other language of your choice. If the folder doesn't exist create one. 
+    So the structure of repository remains consistent
+
+---
+
+## 🎯 Contribution Guidelines
+- Keep your code clean and well-documented.  
+- Use meaningful file names (e.g., `fibonacci.py` not `script1.py`).  
+- Add comments where necessary to help beginners understand.  
+- If submitting a project, include a short `README.md` explaining how it works.  
+
+---
+
+## 🏷 Hacktoberfest
+This repository is **Hacktoberfest-friendly** 💻🎉  
+All accepted PRs will be labeled **hacktoberfest-accepted**.
+
+---
+
+## 📜 License
+This project is licensed under the MIT License — feel free to use the code anywhere with attribution.
+
 ## How to contribute
 1) Fork this repo by clicking the fork button on the top right.
 2) Clone the forked repo on your pc (open a terminal and run this command).
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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "fd0d7a63",
+   "metadata": {},
+   "source": [
+    "Bank marketing dateset taken from UCI  \n",
+    "Link : https://archive.ics.uci.edu/dataset/222/bank+marketing  \n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "4d9b2d88",
+   "metadata": {},
+   "source": [
+    "The data is related with direct marketing campaigns of a Portuguese banking institution. The marketing campaigns were based on phone calls. Often, more than one contact to the same client was required, in order to access if the product (bank term deposit) would be ('yes') or not ('no') subscribed. \n",
+    "The classification goal is to predict if the client will subscribe (yes/no) a term deposit (variable y).\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "643147f7",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "4e9098ea",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "from sklearn.model_selection import train_test_split\n",
+    "from xgboost import XGBClassifier\n",
+    "from sklearn.pipeline import Pipeline\n",
+    "from category_encoders.target_encoder import TargetEncoder\n",
+    "from skopt import BayesSearchCV\n",
+    "from skopt.space import Real, Categorical, Integer\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "5368de6c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#loading dataset\n",
+    "df = pd.read_csv('bank-additional-full.csv', delimiter=';')\n",
+    "#dropping columns that might be less related to desired output\n",
+    "drop_columns = [ 'duration','emp.var.rate', 'cons.price.idx', 'cons.conf.idx', 'euribor3m', 'nr.employed']\n",
+    "#rename columns for better understanding\n",
+    "df = df.rename(columns={'job': 'job_type', 'default': 'default_status',\n",
+    "                                                   'housing': 'housing_loan_status', 'loan': 'personal_loan_status',\n",
+    "                                                   'contact': 'contact_type', 'month': 'contact_month',\n",
+    "                                                   'day_of_week': 'contact_day_of_week', 'campaign': 'num_contacts',\n",
+    "                                                   'pdays': 'days_last_contact', 'previous': 'previous_contacts',\n",
+    "                                                   'poutcome': 'previous_outcome',\n",
+    "                                                   'y': 'result'\n",
+    "                                                    })\n",
+    "# Drop the specified columns\n",
+    "df = df.drop(columns=drop_columns, errors='ignore')\n",
+    "#convert target to numerical values\n",
+    "#specify the column and map its distinct values to numerical values\n",
+    "df['result'] = df['result'].map({'yes':1, 'no':0})"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "0616b74b",
+   "metadata": {},
+   "source": [
+    "Lets look at the dataset now"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "98d0c69e",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>age</th>\n",
+       "      <th>job_type</th>\n",
+       "      <th>marital</th>\n",
+       "      <th>education</th>\n",
+       "      <th>default_status</th>\n",
+       "      <th>housing_loan_status</th>\n",
+       "      <th>personal_loan_status</th>\n",
+       "      <th>contact_type</th>\n",
+       "      <th>contact_month</th>\n",
+       "      <th>contact_day_of_week</th>\n",
+       "      <th>num_contacts</th>\n",
+       "      <th>days_last_contact</th>\n",
+       "      <th>previous_contacts</th>\n",
+       "      <th>previous_outcome</th>\n",
+       "      <th>result</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>56</td>\n",
+       "      <td>housemaid</td>\n",
+       "      <td>married</td>\n",
+       "      <td>basic.4y</td>\n",
+       "      <td>no</td>\n",
+       "      <td>no</td>\n",
+       "      <td>no</td>\n",
+       "      <td>telephone</td>\n",
+       "      <td>may</td>\n",
+       "      <td>mon</td>\n",
+       "      <td>1</td>\n",
+       "      <td>999</td>\n",
+       "      <td>0</td>\n",
+       "      <td>nonexistent</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>57</td>\n",
+       "      <td>services</td>\n",
+       "      <td>married</td>\n",
+       "      <td>high.school</td>\n",
+       "      <td>unknown</td>\n",
+       "      <td>no</td>\n",
+       "      <td>no</td>\n",
+       "      <td>telephone</td>\n",
+       "      <td>may</td>\n",
+       "      <td>mon</td>\n",
+       "      <td>1</td>\n",
+       "      <td>999</td>\n",
+       "      <td>0</td>\n",
+       "      <td>nonexistent</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>37</td>\n",
+       "      <td>services</td>\n",
+       "      <td>married</td>\n",
+       "      <td>high.school</td>\n",
+       "      <td>no</td>\n",
+       "      <td>yes</td>\n",
+       "      <td>no</td>\n",
+       "      <td>telephone</td>\n",
+       "      <td>may</td>\n",
+       "      <td>mon</td>\n",
+       "      <td>1</td>\n",
+       "      <td>999</td>\n",
+       "      <td>0</td>\n",
+       "      <td>nonexistent</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>40</td>\n",
+       "      <td>admin.</td>\n",
+       "      <td>married</td>\n",
+       "      <td>basic.6y</td>\n",
+       "      <td>no</td>\n",
+       "      <td>no</td>\n",
+       "      <td>no</td>\n",
+       "      <td>telephone</td>\n",
+       "      <td>may</td>\n",
+       "      <td>mon</td>\n",
+       "      <td>1</td>\n",
+       "      <td>999</td>\n",
+       "      <td>0</td>\n",
+       "      <td>nonexistent</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>56</td>\n",
+       "      <td>services</td>\n",
+       "      <td>married</td>\n",
+       "      <td>high.school</td>\n",
+       "      <td>no</td>\n",
+       "      <td>no</td>\n",
+       "      <td>yes</td>\n",
+       "      <td>telephone</td>\n",
+       "      <td>may</td>\n",
+       "      <td>mon</td>\n",
+       "      <td>1</td>\n",
+       "      <td>999</td>\n",
+       "      <td>0</td>\n",
+       "      <td>nonexistent</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   age   job_type  marital    education default_status housing_loan_status  \\\n",
+       "0   56  housemaid  married     basic.4y             no                  no   \n",
+       "1   57   services  married  high.school        unknown                  no   \n",
+       "2   37   services  married  high.school             no                 yes   \n",
+       "3   40     admin.  married     basic.6y             no                  no   \n",
+       "4   56   services  married  high.school             no                  no   \n",
+       "\n",
+       "  personal_loan_status contact_type contact_month contact_day_of_week  \\\n",
+       "0                   no    telephone           may                 mon   \n",
+       "1                   no    telephone           may                 mon   \n",
+       "2                   no    telephone           may                 mon   \n",
+       "3                   no    telephone           may                 mon   \n",
+       "4                  yes    telephone           may                 mon   \n",
+       "\n",
+       "   num_contacts  days_last_contact  previous_contacts previous_outcome  result  \n",
+       "0             1                999                  0      nonexistent       0  \n",
+       "1             1                999                  0      nonexistent       0  \n",
+       "2             1                999                  0      nonexistent       0  \n",
+       "3             1                999                  0      nonexistent       0  \n",
+       "4             1                999                  0      nonexistent       0  "
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "c3e9b37b",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "<class 'pandas.core.frame.DataFrame'>\n",
+      "RangeIndex: 41188 entries, 0 to 41187\n",
+      "Data columns (total 15 columns):\n",
+      " #   Column                Non-Null Count  Dtype \n",
+      "---  ------                --------------  ----- \n",
+      " 0   age                   41188 non-null  int64 \n",
+      " 1   job_type              41188 non-null  object\n",
+      " 2   marital               41188 non-null  object\n",
+      " 3   education             41188 non-null  object\n",
+      " 4   default_status        41188 non-null  object\n",
+      " 5   housing_loan_status   41188 non-null  object\n",
+      " 6   personal_loan_status  41188 non-null  object\n",
+      " 7   contact_type          41188 non-null  object\n",
+      " 8   contact_month         41188 non-null  object\n",
+      " 9   contact_day_of_week   41188 non-null  object\n",
+      " 10  num_contacts          41188 non-null  int64 \n",
+      " 11  days_last_contact     41188 non-null  int64 \n",
+      " 12  previous_contacts     41188 non-null  int64 \n",
+      " 13  previous_outcome      41188 non-null  object\n",
+      " 14  result                41188 non-null  int64 \n",
+      "dtypes: int64(5), object(10)\n",
+      "memory usage: 4.7+ MB\n"
+     ]
+    }
+   ],
+   "source": [
+    "df.info()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "29831d95",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "result\n",
+       "0    36548\n",
+       "1     4640\n",
+       "Name: count, dtype: int64"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "df['result'].value_counts()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "2c873e61",
+   "metadata": {},
+   "source": [
+    "Train test split"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "1c94a136",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "X = df.drop(columns=['result'])\n",
+    "y = df['result']\n",
+    "\n",
+    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=8)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "8b800de9",
+   "metadata": {},
+   "source": [
+    "Pipeline"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "96711915",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<style>#sk-container-id-1 {\n",
+       "  /* Definition of color scheme common for light and dark mode */\n",
+       "  --sklearn-color-text: #000;\n",
+       "  --sklearn-color-text-muted: #666;\n",
+       "  --sklearn-color-line: gray;\n",
+       "  /* Definition of color scheme for unfitted estimators */\n",
+       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
+       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
+       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
+       "  --sklearn-color-unfitted-level-3: chocolate;\n",
+       "  /* Definition of color scheme for fitted estimators */\n",
+       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
+       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
+       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
+       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
+       "\n",
+       "  /* Specific color for light theme */\n",
+       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
+       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
+       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
+       "  --sklearn-color-icon: #696969;\n",
+       "\n",
+       "  @media (prefers-color-scheme: dark) {\n",
+       "    /* Redefinition of color scheme for dark theme */\n",
+       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
+       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
+       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
+       "    --sklearn-color-icon: #878787;\n",
+       "  }\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 pre {\n",
+       "  padding: 0;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 input.sk-hidden--visually {\n",
+       "  border: 0;\n",
+       "  clip: rect(1px 1px 1px 1px);\n",
+       "  clip: rect(1px, 1px, 1px, 1px);\n",
+       "  height: 1px;\n",
+       "  margin: -1px;\n",
+       "  overflow: hidden;\n",
+       "  padding: 0;\n",
+       "  position: absolute;\n",
+       "  width: 1px;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-dashed-wrapped {\n",
+       "  border: 1px dashed var(--sklearn-color-line);\n",
+       "  margin: 0 0.4em 0.5em 0.4em;\n",
+       "  box-sizing: border-box;\n",
+       "  padding-bottom: 0.4em;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-container {\n",
+       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
+       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
+       "     so we also need the `!important` here to be able to override the\n",
+       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
+       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
+       "  display: inline-block !important;\n",
+       "  position: relative;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-text-repr-fallback {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       "div.sk-parallel-item,\n",
+       "div.sk-serial,\n",
+       "div.sk-item {\n",
+       "  /* draw centered vertical line to link estimators */\n",
+       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
+       "  background-size: 2px 100%;\n",
+       "  background-repeat: no-repeat;\n",
+       "  background-position: center center;\n",
+       "}\n",
+       "\n",
+       "/* Parallel-specific style estimator block */\n",
+       "\n",
+       "#sk-container-id-1 div.sk-parallel-item::after {\n",
+       "  content: \"\";\n",
+       "  width: 100%;\n",
+       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
+       "  flex-grow: 1;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-parallel {\n",
+       "  display: flex;\n",
+       "  align-items: stretch;\n",
+       "  justify-content: center;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  position: relative;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-parallel-item {\n",
+       "  display: flex;\n",
+       "  flex-direction: column;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-parallel-item:first-child::after {\n",
+       "  align-self: flex-end;\n",
+       "  width: 50%;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-parallel-item:last-child::after {\n",
+       "  align-self: flex-start;\n",
+       "  width: 50%;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-parallel-item:only-child::after {\n",
+       "  width: 0;\n",
+       "}\n",
+       "\n",
+       "/* Serial-specific style estimator block */\n",
+       "\n",
+       "#sk-container-id-1 div.sk-serial {\n",
+       "  display: flex;\n",
+       "  flex-direction: column;\n",
+       "  align-items: center;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  padding-right: 1em;\n",
+       "  padding-left: 1em;\n",
+       "}\n",
+       "\n",
+       "\n",
+       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
+       "clickable and can be expanded/collapsed.\n",
+       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
+       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
+       "*/\n",
+       "\n",
+       "/* Pipeline and ColumnTransformer style (default) */\n",
+       "\n",
+       "#sk-container-id-1 div.sk-toggleable {\n",
+       "  /* Default theme specific background. It is overwritten whether we have a\n",
+       "  specific estimator or a Pipeline/ColumnTransformer */\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "}\n",
+       "\n",
+       "/* Toggleable label */\n",
+       "#sk-container-id-1 label.sk-toggleable__label {\n",
+       "  cursor: pointer;\n",
+       "  display: flex;\n",
+       "  width: 100%;\n",
+       "  margin-bottom: 0;\n",
+       "  padding: 0.5em;\n",
+       "  box-sizing: border-box;\n",
+       "  text-align: center;\n",
+       "  align-items: start;\n",
+       "  justify-content: space-between;\n",
+       "  gap: 0.5em;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 label.sk-toggleable__label .caption {\n",
+       "  font-size: 0.6rem;\n",
+       "  font-weight: lighter;\n",
+       "  color: var(--sklearn-color-text-muted);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 label.sk-toggleable__label-arrow:before {\n",
+       "  /* Arrow on the left of the label */\n",
+       "  content: \"▸\";\n",
+       "  float: left;\n",
+       "  margin-right: 0.25em;\n",
+       "  color: var(--sklearn-color-icon);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "}\n",
+       "\n",
+       "/* Toggleable content - dropdown */\n",
+       "\n",
+       "#sk-container-id-1 div.sk-toggleable__content {\n",
+       "  display: none;\n",
+       "  text-align: left;\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-toggleable__content.fitted {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-toggleable__content pre {\n",
+       "  margin: 0.2em;\n",
+       "  border-radius: 0.25em;\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-toggleable__content.fitted pre {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
+       "  /* Expand drop-down */\n",
+       "  display: block;\n",
+       "  width: 100%;\n",
+       "  overflow: visible;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
+       "  content: \"▾\";\n",
+       "}\n",
+       "\n",
+       "/* Pipeline/ColumnTransformer-specific style */\n",
+       "\n",
+       "#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Estimator-specific style */\n",
+       "\n",
+       "/* Colorize estimator box */\n",
+       "#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-label label.sk-toggleable__label,\n",
+       "#sk-container-id-1 div.sk-label label {\n",
+       "  /* The background is the default theme color */\n",
+       "  color: var(--sklearn-color-text-on-default-background);\n",
+       "}\n",
+       "\n",
+       "/* On hover, darken the color of the background */\n",
+       "#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Label box, darken color on hover, fitted */\n",
+       "#sk-container-id-1 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Estimator label */\n",
+       "\n",
+       "#sk-container-id-1 div.sk-label label {\n",
+       "  font-family: monospace;\n",
+       "  font-weight: bold;\n",
+       "  display: inline-block;\n",
+       "  line-height: 1.2em;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-label-container {\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       "/* Estimator-specific */\n",
+       "#sk-container-id-1 div.sk-estimator {\n",
+       "  font-family: monospace;\n",
+       "  border: 1px dotted var(--sklearn-color-border-box);\n",
+       "  border-radius: 0.25em;\n",
+       "  box-sizing: border-box;\n",
+       "  margin-bottom: 0.5em;\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-estimator.fitted {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "}\n",
+       "\n",
+       "/* on hover */\n",
+       "#sk-container-id-1 div.sk-estimator:hover {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 div.sk-estimator.fitted:hover {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
+       "\n",
+       "/* Common style for \"i\" and \"?\" */\n",
+       "\n",
+       ".sk-estimator-doc-link,\n",
+       "a:link.sk-estimator-doc-link,\n",
+       "a:visited.sk-estimator-doc-link {\n",
+       "  float: right;\n",
+       "  font-size: smaller;\n",
+       "  line-height: 1em;\n",
+       "  font-family: monospace;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  border-radius: 1em;\n",
+       "  height: 1em;\n",
+       "  width: 1em;\n",
+       "  text-decoration: none !important;\n",
+       "  margin-left: 0.5em;\n",
+       "  text-align: center;\n",
+       "  /* unfitted */\n",
+       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
+       "  color: var(--sklearn-color-unfitted-level-1);\n",
+       "}\n",
+       "\n",
+       ".sk-estimator-doc-link.fitted,\n",
+       "a:link.sk-estimator-doc-link.fitted,\n",
+       "a:visited.sk-estimator-doc-link.fitted {\n",
+       "  /* fitted */\n",
+       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
+       "  color: var(--sklearn-color-fitted-level-1);\n",
+       "}\n",
+       "\n",
+       "/* On hover */\n",
+       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
+       ".sk-estimator-doc-link:hover,\n",
+       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
+       ".sk-estimator-doc-link:hover {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
+       "  color: var(--sklearn-color-background);\n",
+       "  text-decoration: none;\n",
+       "}\n",
+       "\n",
+       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
+       ".sk-estimator-doc-link.fitted:hover,\n",
+       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
+       ".sk-estimator-doc-link.fitted:hover {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-3);\n",
+       "  color: var(--sklearn-color-background);\n",
+       "  text-decoration: none;\n",
+       "}\n",
+       "\n",
+       "/* Span, style for the box shown on hovering the info icon */\n",
+       ".sk-estimator-doc-link span {\n",
+       "  display: none;\n",
+       "  z-index: 9999;\n",
+       "  position: relative;\n",
+       "  font-weight: normal;\n",
+       "  right: .2ex;\n",
+       "  padding: .5ex;\n",
+       "  margin: .5ex;\n",
+       "  width: min-content;\n",
+       "  min-width: 20ex;\n",
+       "  max-width: 50ex;\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  box-shadow: 2pt 2pt 4pt #999;\n",
+       "  /* unfitted */\n",
+       "  background: var(--sklearn-color-unfitted-level-0);\n",
+       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
+       "}\n",
+       "\n",
+       ".sk-estimator-doc-link.fitted span {\n",
+       "  /* fitted */\n",
+       "  background: var(--sklearn-color-fitted-level-0);\n",
+       "  border: var(--sklearn-color-fitted-level-3);\n",
+       "}\n",
+       "\n",
+       ".sk-estimator-doc-link:hover span {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
+       "\n",
+       "#sk-container-id-1 a.estimator_doc_link {\n",
+       "  float: right;\n",
+       "  font-size: 1rem;\n",
+       "  line-height: 1em;\n",
+       "  font-family: monospace;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  border-radius: 1rem;\n",
+       "  height: 1rem;\n",
+       "  width: 1rem;\n",
+       "  text-decoration: none;\n",
+       "  /* unfitted */\n",
+       "  color: var(--sklearn-color-unfitted-level-1);\n",
+       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 a.estimator_doc_link.fitted {\n",
+       "  /* fitted */\n",
+       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
+       "  color: var(--sklearn-color-fitted-level-1);\n",
+       "}\n",
+       "\n",
+       "/* On hover */\n",
+       "#sk-container-id-1 a.estimator_doc_link:hover {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
+       "  color: var(--sklearn-color-background);\n",
+       "  text-decoration: none;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-1 a.estimator_doc_link.fitted:hover {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-3);\n",
+       "}\n",
+       "\n",
+       ".estimator-table summary {\n",
+       "    padding: .5rem;\n",
+       "    font-family: monospace;\n",
+       "    cursor: pointer;\n",
+       "}\n",
+       "\n",
+       ".estimator-table details[open] {\n",
+       "    padding-left: 0.1rem;\n",
+       "    padding-right: 0.1rem;\n",
+       "    padding-bottom: 0.3rem;\n",
+       "}\n",
+       "\n",
+       ".estimator-table .parameters-table {\n",
+       "    margin-left: auto !important;\n",
+       "    margin-right: auto !important;\n",
+       "}\n",
+       "\n",
+       ".estimator-table .parameters-table tr:nth-child(odd) {\n",
+       "    background-color: #fff;\n",
+       "}\n",
+       "\n",
+       ".estimator-table .parameters-table tr:nth-child(even) {\n",
+       "    background-color: #f6f6f6;\n",
+       "}\n",
+       "\n",
+       ".estimator-table .parameters-table tr:hover {\n",
+       "    background-color: #e0e0e0;\n",
+       "}\n",
+       "\n",
+       ".estimator-table table td {\n",
+       "    border: 1px solid rgba(106, 105, 104, 0.232);\n",
+       "}\n",
+       "\n",
+       ".user-set td {\n",
+       "    color:rgb(255, 94, 0);\n",
+       "    text-align: left;\n",
+       "}\n",
+       "\n",
+       ".user-set td.value pre {\n",
+       "    color:rgb(255, 94, 0) !important;\n",
+       "    background-color: transparent !important;\n",
+       "}\n",
+       "\n",
+       ".default td {\n",
+       "    color: black;\n",
+       "    text-align: left;\n",
+       "}\n",
+       "\n",
+       ".user-set td i,\n",
+       ".default td i {\n",
+       "    color: black;\n",
+       "}\n",
+       "\n",
+       ".copy-paste-icon {\n",
+       "    background-image: url(data:image/svg+xml;base64,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);\n",
+       "    background-repeat: no-repeat;\n",
+       "    background-size: 14px 14px;\n",
+       "    background-position: 0;\n",
+       "    display: inline-block;\n",
+       "    width: 14px;\n",
+       "    height: 14px;\n",
+       "    cursor: pointer;\n",
+       "}\n",
+       "</style><body><div id=\"sk-container-id-1\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>Pipeline(steps=[(&#x27;encoder&#x27;, TargetEncoder()),\n",
+       "                (&#x27;clf&#x27;,\n",
+       "                 XGBClassifier(base_score=None, booster=None, callbacks=None,\n",
+       "                               colsample_bylevel=None, colsample_bynode=None,\n",
+       "                               colsample_bytree=None, device=None,\n",
+       "                               early_stopping_rounds=None,\n",
+       "                               enable_categorical=False, eval_metric=None,\n",
+       "                               feature_types=None, feature_weights=None,\n",
+       "                               gamma=None, grow_policy=None,\n",
+       "                               importance_type=None,\n",
+       "                               interaction_constraints=None, learning_rate=None,\n",
+       "                               max_bin=None, max_cat_threshold=None,\n",
+       "                               max_cat_to_onehot=None, max_delta_step=None,\n",
+       "                               max_depth=None, max_leaves=None,\n",
+       "                               min_child_weight=None, missing=nan,\n",
+       "                               monotone_constraints=None, multi_strategy=None,\n",
+       "                               n_estimators=None, n_jobs=None,\n",
+       "                               num_parallel_tree=None, ...))])</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label  sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-1\" type=\"checkbox\" ><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label  sk-toggleable__label-arrow\"><div><div>Pipeline</div></div><div><a class=\"sk-estimator-doc-link \" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.7/modules/generated/sklearn.pipeline.Pipeline.html\">?<span>Documentation for Pipeline</span></a><span class=\"sk-estimator-doc-link \">i<span>Not fitted</span></span></div></label><div class=\"sk-toggleable__content \" data-param-prefix=\"\">\n",
+       "        <div class=\"estimator-table\">\n",
+       "            <details>\n",
+       "                <summary>Parameters</summary>\n",
+       "                <table class=\"parameters-table\">\n",
+       "                  <tbody>\n",
+       "                    \n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('steps',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">steps&nbsp;</td>\n",
+       "            <td class=\"value\">[(&#x27;encoder&#x27;, ...), (&#x27;clf&#x27;, ...)]</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('transform_input',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">transform_input&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('memory',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">memory&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('verbose',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">verbose&nbsp;</td>\n",
+       "            <td class=\"value\">False</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "                  </tbody>\n",
+       "                </table>\n",
+       "            </details>\n",
+       "        </div>\n",
+       "    </div></div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator  sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-2\" type=\"checkbox\" ><label for=\"sk-estimator-id-2\" class=\"sk-toggleable__label  sk-toggleable__label-arrow\"><div><div>TargetEncoder</div></div></label><div class=\"sk-toggleable__content \" data-param-prefix=\"encoder__\">\n",
+       "        <div class=\"estimator-table\">\n",
+       "            <details>\n",
+       "                <summary>Parameters</summary>\n",
+       "                <table class=\"parameters-table\">\n",
+       "                  <tbody>\n",
+       "                    \n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('verbose',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">verbose&nbsp;</td>\n",
+       "            <td class=\"value\">0</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('cols',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">cols&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('drop_invariant',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">drop_invariant&nbsp;</td>\n",
+       "            <td class=\"value\">False</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('return_df',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">return_df&nbsp;</td>\n",
+       "            <td class=\"value\">True</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('handle_missing',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">handle_missing&nbsp;</td>\n",
+       "            <td class=\"value\">&#x27;value&#x27;</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('handle_unknown',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">handle_unknown&nbsp;</td>\n",
+       "            <td class=\"value\">&#x27;value&#x27;</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('min_samples_leaf',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">min_samples_leaf&nbsp;</td>\n",
+       "            <td class=\"value\">20</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('smoothing',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">smoothing&nbsp;</td>\n",
+       "            <td class=\"value\">10</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('hierarchy',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">hierarchy&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "                  </tbody>\n",
+       "                </table>\n",
+       "            </details>\n",
+       "        </div>\n",
+       "    </div></div></div><div class=\"sk-item\"><div class=\"sk-estimator  sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-3\" type=\"checkbox\" ><label for=\"sk-estimator-id-3\" class=\"sk-toggleable__label  sk-toggleable__label-arrow\"><div><div>XGBClassifier</div></div><div><a class=\"sk-estimator-doc-link \" rel=\"noreferrer\" target=\"_blank\" href=\"https://xgboost.readthedocs.io/en/release_3.0.0/python/python_api.html#xgboost.XGBClassifier\">?<span>Documentation for XGBClassifier</span></a></div></label><div class=\"sk-toggleable__content \" data-param-prefix=\"clf__\">\n",
+       "        <div class=\"estimator-table\">\n",
+       "            <details>\n",
+       "                <summary>Parameters</summary>\n",
+       "                <table class=\"parameters-table\">\n",
+       "                  <tbody>\n",
+       "                    \n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('objective',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">objective&nbsp;</td>\n",
+       "            <td class=\"value\">&#x27;binary:logistic&#x27;</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('base_score',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">base_score&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('booster',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">booster&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('callbacks',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">callbacks&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('colsample_bylevel',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">colsample_bylevel&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('colsample_bynode',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">colsample_bynode&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('colsample_bytree',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">colsample_bytree&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('device',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">device&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('early_stopping_rounds',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">early_stopping_rounds&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('enable_categorical',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">enable_categorical&nbsp;</td>\n",
+       "            <td class=\"value\">False</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('eval_metric',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">eval_metric&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('feature_types',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">feature_types&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('feature_weights',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">feature_weights&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('gamma',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">gamma&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('grow_policy',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">grow_policy&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('importance_type',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">importance_type&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('interaction_constraints',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">interaction_constraints&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('learning_rate',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">learning_rate&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('max_bin',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">max_bin&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('max_cat_threshold',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">max_cat_threshold&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('max_cat_to_onehot',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">max_cat_to_onehot&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('max_delta_step',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">max_delta_step&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('max_depth',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">max_depth&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('max_leaves',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">max_leaves&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('min_child_weight',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">min_child_weight&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('missing',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">missing&nbsp;</td>\n",
+       "            <td class=\"value\">nan</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('monotone_constraints',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">monotone_constraints&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('multi_strategy',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">multi_strategy&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('n_estimators',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">n_estimators&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('n_jobs',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">n_jobs&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('num_parallel_tree',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">num_parallel_tree&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('random_state',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">random_state&nbsp;</td>\n",
+       "            <td class=\"value\">8</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('reg_alpha',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">reg_alpha&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('reg_lambda',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">reg_lambda&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('sampling_method',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">sampling_method&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('scale_pos_weight',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">scale_pos_weight&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('subsample',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">subsample&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('tree_method',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">tree_method&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('validate_parameters',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">validate_parameters&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('verbosity',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">verbosity&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "                  </tbody>\n",
+       "                </table>\n",
+       "            </details>\n",
+       "        </div>\n",
+       "    </div></div></div></div></div></div></div><script>function copyToClipboard(text, element) {\n",
+       "    // Get the parameter prefix from the closest toggleable content\n",
+       "    const toggleableContent = element.closest('.sk-toggleable__content');\n",
+       "    const paramPrefix = toggleableContent ? toggleableContent.dataset.paramPrefix : '';\n",
+       "    const fullParamName = paramPrefix ? `${paramPrefix}${text}` : text;\n",
+       "\n",
+       "    const originalStyle = element.style;\n",
+       "    const computedStyle = window.getComputedStyle(element);\n",
+       "    const originalWidth = computedStyle.width;\n",
+       "    const originalHTML = element.innerHTML.replace('Copied!', '');\n",
+       "\n",
+       "    navigator.clipboard.writeText(fullParamName)\n",
+       "        .then(() => {\n",
+       "            element.style.width = originalWidth;\n",
+       "            element.style.color = 'green';\n",
+       "            element.innerHTML = \"Copied!\";\n",
+       "\n",
+       "            setTimeout(() => {\n",
+       "                element.innerHTML = originalHTML;\n",
+       "                element.style = originalStyle;\n",
+       "            }, 2000);\n",
+       "        })\n",
+       "        .catch(err => {\n",
+       "            console.error('Failed to copy:', err);\n",
+       "            element.style.color = 'red';\n",
+       "            element.innerHTML = \"Failed!\";\n",
+       "            setTimeout(() => {\n",
+       "                element.innerHTML = originalHTML;\n",
+       "                element.style = originalStyle;\n",
+       "            }, 2000);\n",
+       "        });\n",
+       "    return false;\n",
+       "}\n",
+       "\n",
+       "document.querySelectorAll('.fa-regular.fa-copy').forEach(function(element) {\n",
+       "    const toggleableContent = element.closest('.sk-toggleable__content');\n",
+       "    const paramPrefix = toggleableContent ? toggleableContent.dataset.paramPrefix : '';\n",
+       "    const paramName = element.parentElement.nextElementSibling.textContent.trim();\n",
+       "    const fullParamName = paramPrefix ? `${paramPrefix}${paramName}` : paramName;\n",
+       "\n",
+       "    element.setAttribute('title', fullParamName);\n",
+       "});\n",
+       "</script></body>"
+      ],
+      "text/plain": [
+       "Pipeline(steps=[('encoder', TargetEncoder()),\n",
+       "                ('clf',\n",
+       "                 XGBClassifier(base_score=None, booster=None, callbacks=None,\n",
+       "                               colsample_bylevel=None, colsample_bynode=None,\n",
+       "                               colsample_bytree=None, device=None,\n",
+       "                               early_stopping_rounds=None,\n",
+       "                               enable_categorical=False, eval_metric=None,\n",
+       "                               feature_types=None, feature_weights=None,\n",
+       "                               gamma=None, grow_policy=None,\n",
+       "                               importance_type=None,\n",
+       "                               interaction_constraints=None, learning_rate=None,\n",
+       "                               max_bin=None, max_cat_threshold=None,\n",
+       "                               max_cat_to_onehot=None, max_delta_step=None,\n",
+       "                               max_depth=None, max_leaves=None,\n",
+       "                               min_child_weight=None, missing=nan,\n",
+       "                               monotone_constraints=None, multi_strategy=None,\n",
+       "                               n_estimators=None, n_jobs=None,\n",
+       "                               num_parallel_tree=None, ...))])"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "estimators = [\n",
+    "    ('encoder', TargetEncoder()),\n",
+    "    ('clf', XGBClassifier(random_state=8)) # can customize objective function with the objective parameter\n",
+    "]\n",
+    "pipe = Pipeline(steps=estimators)\n",
+    "pipe"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5697f92a",
+   "metadata": {},
+   "source": [
+    "Hyper Parameter Tuning"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "ae23227a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "search_space = {#within the estimator calling the parameters, Clf is the name of the classifier \n",
+    "#    previously defined in the pipeline\n",
+    "    'clf__max_depth': Integer(2,8),\n",
+    "    'clf__learning_rate': Real(0.001, 1.0, prior='log-uniform'),\n",
+    "    'clf__subsample': Real(0.5, 1.0),\n",
+    "    'clf__colsample_bytree': Real(0.5, 1.0),\n",
+    "    'clf__colsample_bylevel': Real(0.5, 1.0),\n",
+    "    'clf__colsample_bynode' : Real(0.5, 1.0),\n",
+    "    'clf__reg_alpha': Real(0.0, 10.0),\n",
+    "    'clf__reg_lambda': Real(0.0, 10.0),\n",
+    "    'clf__gamma': Real(0.0, 10.0)\n",
+    "}\n",
+    "#Note: The search space can be customized based on the specific needs of the model and the dataset.\n",
+    "#BayesSearchCV is used for hyperparameter tuning using Bayesian optimization\n",
+    "#It allows for efficient exploration of the hyperparameter space.\n",
+    "#bayes_search requirese pipeline and search space to be defined\n",
+    "opt = BayesSearchCV(\n",
+    "    estimator=pipe,\n",
+    "    search_spaces=search_space,\n",
+    "    n_iter=30,\n",
+    "    scoring='roc_auc',               \n",
+    "    cv=3,\n",
+    "    n_jobs=-1,\n",
+    "    random_state=8,\n",
+    "    verbose=2,\n",
+    "    return_train_score=True,\n",
+    "    #is_classifier=True\n",
+    ")\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "351702bb",
+   "metadata": {},
+   "source": [
+    "Train the XGBoost model"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "026d07ad",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Fitting 3 folds for each of 1 candidates, totalling 3 fits\n",
+      "[CV] END clf__colsample_bylevel=0.5331080642783614, clf__colsample_bynode=0.7262320733948379, clf__colsample_bytree=0.5362052518135637, clf__gamma=7.436578137661654, clf__learning_rate=0.0011002938624638172, clf__max_depth=5, clf__reg_alpha=5.016505750780453, clf__reg_lambda=1.964788283871643, clf__subsample=0.5258638996089925; total time=   0.4s\n",
+      "[CV] END clf__colsample_bylevel=0.5331080642783614, clf__colsample_bynode=0.7262320733948379, clf__colsample_bytree=0.5362052518135637, clf__gamma=7.436578137661654, clf__learning_rate=0.0011002938624638172, clf__max_depth=5, clf__reg_alpha=5.016505750780453, clf__reg_lambda=1.964788283871643, clf__subsample=0.5258638996089925; total time=   0.4s\n",
+      "[CV] END clf__colsample_bylevel=0.5331080642783614, clf__colsample_bynode=0.7262320733948379, clf__colsample_bytree=0.5362052518135637, clf__gamma=7.436578137661654, clf__learning_rate=0.0011002938624638172, clf__max_depth=5, clf__reg_alpha=5.016505750780453, clf__reg_lambda=1.964788283871643, clf__subsample=0.5258638996089925; total time=   0.4s\n",
+      "Fitting 3 folds for each of 1 candidates, totalling 3 fits\n",
+      "[CV] END clf__colsample_bylevel=0.7098720980049984, clf__colsample_bynode=0.5395172405909037, clf__colsample_bytree=0.5048675793234745, clf__gamma=3.4426412862156925, clf__learning_rate=0.002566198468819385, clf__max_depth=4, clf__reg_alpha=6.94019423320267, clf__reg_lambda=1.9029714271812788, clf__subsample=0.8480768493236798; total time=   0.4s\n",
+      "[CV] END clf__colsample_bylevel=0.7098720980049984, clf__colsample_bynode=0.5395172405909037, clf__colsample_bytree=0.5048675793234745, clf__gamma=3.4426412862156925, clf__learning_rate=0.002566198468819385, clf__max_depth=4, clf__reg_alpha=6.94019423320267, clf__reg_lambda=1.9029714271812788, clf__subsample=0.8480768493236798; total time=   0.4s\n",
+      "[CV] END clf__colsample_bylevel=0.7098720980049984, clf__colsample_bynode=0.5395172405909037, clf__colsample_bytree=0.5048675793234745, clf__gamma=3.4426412862156925, clf__learning_rate=0.002566198468819385, clf__max_depth=4, clf__reg_alpha=6.94019423320267, clf__reg_lambda=1.9029714271812788, clf__subsample=0.8480768493236798; total time=   0.4s\n",
+      "Fitting 3 folds for each of 1 candidates, totalling 3 fits\n",
+      "[CV] END clf__colsample_bylevel=0.6301181140809947, clf__colsample_bynode=0.7703817113387359, clf__colsample_bytree=0.506103014140404, clf__gamma=2.079165271399323, clf__learning_rate=0.0031574039841631043, clf__max_depth=3, clf__reg_alpha=3.9908788581451304, clf__reg_lambda=4.068904354579378, clf__subsample=0.691339226818626; total time=   0.4s\n",
+      "[CV] END clf__colsample_bylevel=0.6301181140809947, clf__colsample_bynode=0.7703817113387359, clf__colsample_bytree=0.506103014140404, clf__gamma=2.079165271399323, clf__learning_rate=0.0031574039841631043, clf__max_depth=3, clf__reg_alpha=3.9908788581451304, clf__reg_lambda=4.068904354579378, clf__subsample=0.691339226818626; total time=   0.3s\n",
+      "[CV] END clf__colsample_bylevel=0.6301181140809947, clf__colsample_bynode=0.7703817113387359, clf__colsample_bytree=0.506103014140404, clf__gamma=2.079165271399323, clf__learning_rate=0.0031574039841631043, clf__max_depth=3, clf__reg_alpha=3.9908788581451304, clf__reg_lambda=4.068904354579378, clf__subsample=0.691339226818626; total time=   0.3s\n",
+      "Fitting 3 folds for each of 1 candidates, totalling 3 fits\n",
+      "[CV] END clf__colsample_bylevel=0.7750018497221565, clf__colsample_bynode=0.5614437441596264, clf__colsample_bytree=0.9126202065825759, clf__gamma=8.289497472648083, clf__learning_rate=0.4299244814327041, clf__max_depth=6, clf__reg_alpha=2.784887532399771, clf__reg_lambda=1.67027558902639, clf__subsample=0.5966102807384807; total time=   0.3s\n",
+      "[CV] END clf__colsample_bylevel=0.7750018497221565, clf__colsample_bynode=0.5614437441596264, clf__colsample_bytree=0.9126202065825759, clf__gamma=8.289497472648083, clf__learning_rate=0.4299244814327041, clf__max_depth=6, clf__reg_alpha=2.784887532399771, clf__reg_lambda=1.67027558902639, clf__subsample=0.5966102807384807; total time=   0.3s\n",
+      "[CV] END clf__colsample_bylevel=0.7750018497221565, clf__colsample_bynode=0.5614437441596264, clf__colsample_bytree=0.9126202065825759, clf__gamma=8.289497472648083, clf__learning_rate=0.4299244814327041, clf__max_depth=6, clf__reg_alpha=2.784887532399771, clf__reg_lambda=1.67027558902639, clf__subsample=0.5966102807384807; total time=   0.3s\n",
+      "Fitting 3 folds for each of 1 candidates, totalling 3 fits\n",
+      "[CV] END clf__colsample_bylevel=0.9425384185492701, clf__colsample_bynode=0.9095956806239844, clf__colsample_bytree=0.706128679361455, clf__gamma=1.6598135411398998, clf__learning_rate=0.7929828265552742, clf__max_depth=7, clf__reg_alpha=6.127334959237263, clf__reg_lambda=4.20954286031855, clf__subsample=0.9992625073567596; total time=   0.3s\n",
+      "[CV] END clf__colsample_bylevel=0.9425384185492701, clf__colsample_bynode=0.9095956806239844, clf__colsample_bytree=0.706128679361455, clf__gamma=1.6598135411398998, clf__learning_rate=0.7929828265552742, clf__max_depth=7, clf__reg_alpha=6.127334959237263, clf__reg_lambda=4.20954286031855, clf__subsample=0.9992625073567596; total time=   0.3s\n",
+      "[CV] END clf__colsample_bylevel=0.9425384185492701, clf__colsample_bynode=0.9095956806239844, clf__colsample_bytree=0.706128679361455, clf__gamma=1.6598135411398998, clf__learning_rate=0.7929828265552742, clf__max_depth=7, clf__reg_alpha=6.127334959237263, clf__reg_lambda=4.20954286031855, clf__subsample=0.9992625073567596; total time=   0.3s\n",
+      "Fitting 3 folds for each of 1 candidates, totalling 3 fits\n",
+      "[CV] END clf__colsample_bylevel=0.5056087634867006, clf__colsample_bynode=0.6000722403604478, clf__colsample_bytree=0.7220415864598968, clf__gamma=5.107918246929528, clf__learning_rate=0.00770902165228149, clf__max_depth=3, clf__reg_alpha=7.419482800525566, clf__reg_lambda=5.853383854066662, clf__subsample=0.9585647835362849; total time=   0.3s\n",
+      "[CV] END clf__colsample_bylevel=0.5056087634867006, clf__colsample_bynode=0.6000722403604478, clf__colsample_bytree=0.7220415864598968, clf__gamma=5.107918246929528, clf__learning_rate=0.00770902165228149, clf__max_depth=3, clf__reg_alpha=7.419482800525566, clf__reg_lambda=5.853383854066662, clf__subsample=0.9585647835362849; total time=   0.3s\n",
+      "[CV] END clf__colsample_bylevel=0.5056087634867006, clf__colsample_bynode=0.6000722403604478, clf__colsample_bytree=0.7220415864598968, clf__gamma=5.107918246929528, clf__learning_rate=0.00770902165228149, clf__max_depth=3, clf__reg_alpha=7.419482800525566, clf__reg_lambda=5.853383854066662, clf__subsample=0.9585647835362849; total time=   0.3s\n",
+      "Fitting 3 folds for each of 1 candidates, totalling 3 fits\n",
+      "[CV] END clf__colsample_bylevel=0.935225370284509, clf__colsample_bynode=0.5390519575908672, clf__colsample_bytree=0.6298025462003691, clf__gamma=8.638048955941981, clf__learning_rate=0.014685268484248162, clf__max_depth=6, clf__reg_alpha=9.596594920803778, clf__reg_lambda=1.7891228625458846, clf__subsample=0.6457705718332348; total time=   0.3s\n",
+      "[CV] END clf__colsample_bylevel=0.935225370284509, clf__colsample_bynode=0.5390519575908672, clf__colsample_bytree=0.6298025462003691, clf__gamma=8.638048955941981, clf__learning_rate=0.014685268484248162, clf__max_depth=6, clf__reg_alpha=9.596594920803778, clf__reg_lambda=1.7891228625458846, clf__subsample=0.6457705718332348; total time=   0.3s\n",
+      "[CV] END clf__colsample_bylevel=0.935225370284509, clf__colsample_bynode=0.5390519575908672, clf__colsample_bytree=0.6298025462003691, clf__gamma=8.638048955941981, clf__learning_rate=0.014685268484248162, clf__max_depth=6, clf__reg_alpha=9.596594920803778, clf__reg_lambda=1.7891228625458846, clf__subsample=0.6457705718332348; total time=   0.3s\n",
+      "Fitting 3 folds for each of 1 candidates, totalling 3 fits\n",
+      "[CV] END clf__colsample_bylevel=0.8255063664935096, clf__colsample_bynode=0.9566459979367115, clf__colsample_bytree=0.7745652753956729, clf__gamma=9.034580483401264, clf__learning_rate=0.02796171154881776, clf__max_depth=2, clf__reg_alpha=2.3562893513108114, clf__reg_lambda=7.616125300822734, clf__subsample=0.5252342481879482; total time=   0.3s\n",
+      "[CV] END clf__colsample_bylevel=0.8255063664935096, clf__colsample_bynode=0.9566459979367115, clf__colsample_bytree=0.7745652753956729, clf__gamma=9.034580483401264, clf__learning_rate=0.02796171154881776, clf__max_depth=2, clf__reg_alpha=2.3562893513108114, clf__reg_lambda=7.616125300822734, clf__subsample=0.5252342481879482; total time=   0.3s\n",
+      "[CV] END clf__colsample_bylevel=0.8255063664935096, clf__colsample_bynode=0.9566459979367115, clf__colsample_bytree=0.7745652753956729, clf__gamma=9.034580483401264, clf__learning_rate=0.02796171154881776, clf__max_depth=2, clf__reg_alpha=2.3562893513108114, clf__reg_lambda=7.616125300822734, clf__subsample=0.5252342481879482; total time=   0.3s\n",
+      "Fitting 3 folds for each of 1 candidates, totalling 3 fits\n",
+      "[CV] END clf__colsample_bylevel=0.7160044460033754, clf__colsample_bynode=0.5634842539270097, clf__colsample_bytree=0.8894150401192538, clf__gamma=0.12840880628708476, clf__learning_rate=0.006917774244564682, clf__max_depth=4, clf__reg_alpha=9.964867597661469, clf__reg_lambda=9.039217490191113, clf__subsample=0.7399361526500796; total time=   0.3s\n",
+      "[CV] END clf__colsample_bylevel=0.7160044460033754, clf__colsample_bynode=0.5634842539270097, clf__colsample_bytree=0.8894150401192538, clf__gamma=0.12840880628708476, clf__learning_rate=0.006917774244564682, clf__max_depth=4, clf__reg_alpha=9.964867597661469, clf__reg_lambda=9.039217490191113, clf__subsample=0.7399361526500796; total time=   0.3s\n",
+      "[CV] END clf__colsample_bylevel=0.7160044460033754, clf__colsample_bynode=0.5634842539270097, clf__colsample_bytree=0.8894150401192538, clf__gamma=0.12840880628708476, clf__learning_rate=0.006917774244564682, clf__max_depth=4, clf__reg_alpha=9.964867597661469, clf__reg_lambda=9.039217490191113, clf__subsample=0.7399361526500796; total time=   0.3s\n",
+      "Fitting 3 folds for each of 1 candidates, totalling 3 fits\n",
+      "[CV] END clf__colsample_bylevel=0.6854728136721551, clf__colsample_bynode=0.9716292421559054, clf__colsample_bytree=0.9999681720272138, clf__gamma=9.269342703724346, clf__learning_rate=0.4165635668761467, clf__max_depth=5, clf__reg_alpha=9.90967391483027, clf__reg_lambda=9.617478139041276, clf__subsample=0.7406323564767542; total time=   0.3s\n",
+      "[CV] END clf__colsample_bylevel=0.6854728136721551, clf__colsample_bynode=0.9716292421559054, clf__colsample_bytree=0.9999681720272138, clf__gamma=9.269342703724346, clf__learning_rate=0.4165635668761467, clf__max_depth=5, clf__reg_alpha=9.90967391483027, clf__reg_lambda=9.617478139041276, clf__subsample=0.7406323564767542; total time=   0.3s\n",
+      "[CV] END clf__colsample_bylevel=0.6854728136721551, clf__colsample_bynode=0.9716292421559054, clf__colsample_bytree=0.9999681720272138, clf__gamma=9.269342703724346, clf__learning_rate=0.4165635668761467, clf__max_depth=5, clf__reg_alpha=9.90967391483027, clf__reg_lambda=9.617478139041276, clf__subsample=0.7406323564767542; total time=   0.3s\n",
+      "Fitting 3 folds for each of 1 candidates, totalling 3 fits\n",
+      "[CV] END clf__colsample_bylevel=0.7723018676832343, clf__colsample_bynode=0.7730488247401104, clf__colsample_bytree=0.912288322775457, clf__gamma=0.09283704456179322, clf__learning_rate=0.22456104337268815, clf__max_depth=3, clf__reg_alpha=0.13080555109971195, clf__reg_lambda=3.0680973538012397, clf__subsample=0.9696264100257488; total time=   0.4s\n",
+      "[CV] END clf__colsample_bylevel=0.7723018676832343, clf__colsample_bynode=0.7730488247401104, clf__colsample_bytree=0.912288322775457, clf__gamma=0.09283704456179322, clf__learning_rate=0.22456104337268815, clf__max_depth=3, clf__reg_alpha=0.13080555109971195, clf__reg_lambda=3.0680973538012397, clf__subsample=0.9696264100257488; total time=   0.4s\n",
+      "[CV] END clf__colsample_bylevel=0.7723018676832343, clf__colsample_bynode=0.7730488247401104, clf__colsample_bytree=0.912288322775457, clf__gamma=0.09283704456179322, clf__learning_rate=0.22456104337268815, clf__max_depth=3, clf__reg_alpha=0.13080555109971195, clf__reg_lambda=3.0680973538012397, clf__subsample=0.9696264100257488; total time=   0.3s\n",
+      "Fitting 3 folds for each of 1 candidates, totalling 3 fits\n",
+      "[CV] END clf__colsample_bylevel=0.5869045459755697, clf__colsample_bynode=0.8634774697005057, clf__colsample_bytree=0.9403618922982758, clf__gamma=1.8527618162736694, clf__learning_rate=0.06955243801357099, clf__max_depth=8, clf__reg_alpha=9.814121464631345, clf__reg_lambda=2.2241111004546306, clf__subsample=0.5050099833110352; total time=   0.4s\n",
+      "[CV] END clf__colsample_bylevel=0.5869045459755697, clf__colsample_bynode=0.8634774697005057, clf__colsample_bytree=0.9403618922982758, clf__gamma=1.8527618162736694, clf__learning_rate=0.06955243801357099, clf__max_depth=8, clf__reg_alpha=9.814121464631345, clf__reg_lambda=2.2241111004546306, clf__subsample=0.5050099833110352; total time=   0.4s\n",
+      "[CV] END clf__colsample_bylevel=0.5869045459755697, clf__colsample_bynode=0.8634774697005057, clf__colsample_bytree=0.9403618922982758, clf__gamma=1.8527618162736694, clf__learning_rate=0.06955243801357099, clf__max_depth=8, clf__reg_alpha=9.814121464631345, clf__reg_lambda=2.2241111004546306, clf__subsample=0.5050099833110352; total time=   0.4s\n",
+      "Fitting 3 folds for each of 1 candidates, totalling 3 fits\n",
+      "[CV] END clf__colsample_bylevel=0.6577260490846814, clf__colsample_bynode=0.9459504140934167, clf__colsample_bytree=0.6889735593644536, clf__gamma=0.0, clf__learning_rate=0.14138755527281946, clf__max_depth=8, clf__reg_alpha=8.909470446776664, clf__reg_lambda=10.0, clf__subsample=0.6548185101793; total time=   0.5s\n",
+      "[CV] END clf__colsample_bylevel=0.6577260490846814, clf__colsample_bynode=0.9459504140934167, clf__colsample_bytree=0.6889735593644536, clf__gamma=0.0, clf__learning_rate=0.14138755527281946, clf__max_depth=8, clf__reg_alpha=8.909470446776664, clf__reg_lambda=10.0, clf__subsample=0.6548185101793; total time=   0.4s\n",
+      "[CV] END clf__colsample_bylevel=0.6577260490846814, clf__colsample_bynode=0.9459504140934167, clf__colsample_bytree=0.6889735593644536, clf__gamma=0.0, clf__learning_rate=0.14138755527281946, clf__max_depth=8, clf__reg_alpha=8.909470446776664, clf__reg_lambda=10.0, clf__subsample=0.6548185101793; total time=   0.4s\n",
+      "Fitting 3 folds for each of 1 candidates, totalling 3 fits\n",
+      "[CV] END clf__colsample_bylevel=0.6760642200903499, clf__colsample_bynode=0.7217263801593097, clf__colsample_bytree=0.5, clf__gamma=0.0, clf__learning_rate=0.1302835423378258, clf__max_depth=3, clf__reg_alpha=9.815881203730958, clf__reg_lambda=0.0, clf__subsample=0.6358797096074176; total time=   0.4s\n",
+      "[CV] END clf__colsample_bylevel=0.6760642200903499, clf__colsample_bynode=0.7217263801593097, clf__colsample_bytree=0.5, clf__gamma=0.0, clf__learning_rate=0.1302835423378258, clf__max_depth=3, clf__reg_alpha=9.815881203730958, clf__reg_lambda=0.0, clf__subsample=0.6358797096074176; total time=   0.4s\n",
+      "[CV] END clf__colsample_bylevel=0.6760642200903499, clf__colsample_bynode=0.7217263801593097, clf__colsample_bytree=0.5, clf__gamma=0.0, clf__learning_rate=0.1302835423378258, clf__max_depth=3, clf__reg_alpha=9.815881203730958, clf__reg_lambda=0.0, clf__subsample=0.6358797096074176; total time=   0.4s\n",
+      "Fitting 3 folds for each of 1 candidates, totalling 3 fits\n",
+      "[CV] END clf__colsample_bylevel=0.5845839656611151, clf__colsample_bynode=0.7250250762103452, clf__colsample_bytree=0.9981700248106462, clf__gamma=9.556525989245547, clf__learning_rate=0.0010843112498718414, clf__max_depth=3, clf__reg_alpha=0.14735290535317305, clf__reg_lambda=9.238814536694226, clf__subsample=0.8995049367387801; total time=   0.3s\n",
+      "[CV] END clf__colsample_bylevel=0.5845839656611151, clf__colsample_bynode=0.7250250762103452, clf__colsample_bytree=0.9981700248106462, clf__gamma=9.556525989245547, clf__learning_rate=0.0010843112498718414, clf__max_depth=3, clf__reg_alpha=0.14735290535317305, clf__reg_lambda=9.238814536694226, clf__subsample=0.8995049367387801; total time=   0.4s\n",
+      "[CV] END clf__colsample_bylevel=0.5845839656611151, clf__colsample_bynode=0.7250250762103452, clf__colsample_bytree=0.9981700248106462, clf__gamma=9.556525989245547, clf__learning_rate=0.0010843112498718414, clf__max_depth=3, clf__reg_alpha=0.14735290535317305, clf__reg_lambda=9.238814536694226, clf__subsample=0.8995049367387801; total time=   0.4s\n",
+      "Fitting 3 folds for each of 1 candidates, totalling 3 fits\n",
+      "[CV] END clf__colsample_bylevel=0.5854967726735413, clf__colsample_bynode=0.7024935828670682, clf__colsample_bytree=0.5035777836647117, clf__gamma=9.849773665864356, clf__learning_rate=0.8756258419501888, clf__max_depth=8, clf__reg_alpha=7.504721094219438, clf__reg_lambda=5.911145882951871, clf__subsample=0.5683773486467666; total time=   0.4s\n",
+      "[CV] END clf__colsample_bylevel=0.5854967726735413, clf__colsample_bynode=0.7024935828670682, clf__colsample_bytree=0.5035777836647117, clf__gamma=9.849773665864356, clf__learning_rate=0.8756258419501888, clf__max_depth=8, clf__reg_alpha=7.504721094219438, clf__reg_lambda=5.911145882951871, clf__subsample=0.5683773486467666; total time=   0.4s\n",
+      "[CV] END clf__colsample_bylevel=0.5854967726735413, clf__colsample_bynode=0.7024935828670682, clf__colsample_bytree=0.5035777836647117, clf__gamma=9.849773665864356, clf__learning_rate=0.8756258419501888, clf__max_depth=8, clf__reg_alpha=7.504721094219438, clf__reg_lambda=5.911145882951871, clf__subsample=0.5683773486467666; total time=   0.4s\n",
+      "Fitting 3 folds for each of 1 candidates, totalling 3 fits\n",
+      "[CV] END clf__colsample_bylevel=0.5402378105451193, clf__colsample_bynode=0.604715085125622, clf__colsample_bytree=1.0, clf__gamma=2.659735482461985, clf__learning_rate=1.0, clf__max_depth=5, clf__reg_alpha=6.894319369891445, clf__reg_lambda=7.265511387449289, clf__subsample=0.568226551334247; total time=   0.4s\n",
+      "[CV] END clf__colsample_bylevel=0.5402378105451193, clf__colsample_bynode=0.604715085125622, clf__colsample_bytree=1.0, clf__gamma=2.659735482461985, clf__learning_rate=1.0, clf__max_depth=5, clf__reg_alpha=6.894319369891445, clf__reg_lambda=7.265511387449289, clf__subsample=0.568226551334247; total time=   0.3s\n",
+      "[CV] END clf__colsample_bylevel=0.5402378105451193, clf__colsample_bynode=0.604715085125622, clf__colsample_bytree=1.0, clf__gamma=2.659735482461985, clf__learning_rate=1.0, clf__max_depth=5, clf__reg_alpha=6.894319369891445, clf__reg_lambda=7.265511387449289, clf__subsample=0.568226551334247; total time=   0.4s\n",
+      "Fitting 3 folds for each of 1 candidates, totalling 3 fits\n",
+      "[CV] END clf__colsample_bylevel=0.5087587974541569, clf__colsample_bynode=0.8004961908213178, clf__colsample_bytree=0.9188630786243432, clf__gamma=4.638212225913446, clf__learning_rate=0.5792966022904099, clf__max_depth=8, clf__reg_alpha=1.5878836678255284, clf__reg_lambda=3.0728173518354436, clf__subsample=1.0; total time=   0.4s\n",
+      "[CV] END clf__colsample_bylevel=0.5087587974541569, clf__colsample_bynode=0.8004961908213178, clf__colsample_bytree=0.9188630786243432, clf__gamma=4.638212225913446, clf__learning_rate=0.5792966022904099, clf__max_depth=8, clf__reg_alpha=1.5878836678255284, clf__reg_lambda=3.0728173518354436, clf__subsample=1.0; total time=   0.3s\n",
+      "[CV] END clf__colsample_bylevel=0.5087587974541569, clf__colsample_bynode=0.8004961908213178, clf__colsample_bytree=0.9188630786243432, clf__gamma=4.638212225913446, clf__learning_rate=0.5792966022904099, clf__max_depth=8, clf__reg_alpha=1.5878836678255284, clf__reg_lambda=3.0728173518354436, clf__subsample=1.0; total time=   0.3s\n",
+      "Fitting 3 folds for each of 1 candidates, totalling 3 fits\n",
+      "[CV] END clf__colsample_bylevel=0.7157221399304734, clf__colsample_bynode=0.828021086306063, clf__colsample_bytree=0.9226383881368138, clf__gamma=0.0, clf__learning_rate=1.0, clf__max_depth=3, clf__reg_alpha=9.058785882891943, clf__reg_lambda=9.859891434716468, clf__subsample=0.5716700977212141; total time=   0.4s\n",
+      "[CV] END clf__colsample_bylevel=0.7157221399304734, clf__colsample_bynode=0.828021086306063, clf__colsample_bytree=0.9226383881368138, clf__gamma=0.0, clf__learning_rate=1.0, clf__max_depth=3, clf__reg_alpha=9.058785882891943, clf__reg_lambda=9.859891434716468, clf__subsample=0.5716700977212141; total time=   0.4s\n",
+      "[CV] END clf__colsample_bylevel=0.7157221399304734, clf__colsample_bynode=0.828021086306063, clf__colsample_bytree=0.9226383881368138, clf__gamma=0.0, clf__learning_rate=1.0, clf__max_depth=3, clf__reg_alpha=9.058785882891943, clf__reg_lambda=9.859891434716468, clf__subsample=0.5716700977212141; total time=   0.5s\n",
+      "Fitting 3 folds for each of 1 candidates, totalling 3 fits\n",
+      "[CV] END clf__colsample_bylevel=1.0, clf__colsample_bynode=0.8398024088381104, clf__colsample_bytree=1.0, clf__gamma=0.0, clf__learning_rate=0.12472446448987655, clf__max_depth=8, clf__reg_alpha=10.0, clf__reg_lambda=9.900646330789474, clf__subsample=1.0; total time=   0.5s\n",
+      "[CV] END clf__colsample_bylevel=1.0, clf__colsample_bynode=0.8398024088381104, clf__colsample_bytree=1.0, clf__gamma=0.0, clf__learning_rate=0.12472446448987655, clf__max_depth=8, clf__reg_alpha=10.0, clf__reg_lambda=9.900646330789474, clf__subsample=1.0; total time=   0.4s\n",
+      "[CV] END clf__colsample_bylevel=1.0, clf__colsample_bynode=0.8398024088381104, clf__colsample_bytree=1.0, clf__gamma=0.0, clf__learning_rate=0.12472446448987655, clf__max_depth=8, clf__reg_alpha=10.0, clf__reg_lambda=9.900646330789474, clf__subsample=1.0; total time=   0.5s\n",
+      "Fitting 3 folds for each of 1 candidates, totalling 3 fits\n",
+      "[CV] END clf__colsample_bylevel=1.0, clf__colsample_bynode=0.7648740843304054, clf__colsample_bytree=1.0, clf__gamma=0.0, clf__learning_rate=0.13509903788527342, clf__max_depth=5, clf__reg_alpha=8.919375149500015, clf__reg_lambda=2.481813646400672, clf__subsample=0.5; total time=   0.5s\n",
+      "[CV] END clf__colsample_bylevel=1.0, clf__colsample_bynode=0.7648740843304054, clf__colsample_bytree=1.0, clf__gamma=0.0, clf__learning_rate=0.13509903788527342, clf__max_depth=5, clf__reg_alpha=8.919375149500015, clf__reg_lambda=2.481813646400672, clf__subsample=0.5; total time=   0.5s\n",
+      "[CV] END clf__colsample_bylevel=1.0, clf__colsample_bynode=0.7648740843304054, clf__colsample_bytree=1.0, clf__gamma=0.0, clf__learning_rate=0.13509903788527342, clf__max_depth=5, clf__reg_alpha=8.919375149500015, clf__reg_lambda=2.481813646400672, clf__subsample=0.5; total time=   0.4s\n",
+      "Fitting 3 folds for each of 1 candidates, totalling 3 fits\n",
+      "[CV] END clf__colsample_bylevel=0.9358894420963616, clf__colsample_bynode=0.855282118547783, clf__colsample_bytree=1.0, clf__gamma=0.0, clf__learning_rate=0.08435283462541183, clf__max_depth=6, clf__reg_alpha=1.2079974432107585, clf__reg_lambda=5.793583799464579, clf__subsample=0.978466442740766; total time=   0.4s\n",
+      "[CV] END clf__colsample_bylevel=0.9358894420963616, clf__colsample_bynode=0.855282118547783, clf__colsample_bytree=1.0, clf__gamma=0.0, clf__learning_rate=0.08435283462541183, clf__max_depth=6, clf__reg_alpha=1.2079974432107585, clf__reg_lambda=5.793583799464579, clf__subsample=0.978466442740766; total time=   0.4s\n",
+      "[CV] END clf__colsample_bylevel=0.9358894420963616, clf__colsample_bynode=0.855282118547783, clf__colsample_bytree=1.0, clf__gamma=0.0, clf__learning_rate=0.08435283462541183, clf__max_depth=6, clf__reg_alpha=1.2079974432107585, clf__reg_lambda=5.793583799464579, clf__subsample=0.978466442740766; total time=   0.4s\n",
+      "Fitting 3 folds for each of 1 candidates, totalling 3 fits\n",
+      "[CV] END clf__colsample_bylevel=0.5091891994585076, clf__colsample_bynode=0.8942779420776591, clf__colsample_bytree=0.9585526976941942, clf__gamma=0.09704478950707737, clf__learning_rate=0.001082794871840973, clf__max_depth=5, clf__reg_alpha=9.274914215839157, clf__reg_lambda=2.1283026903659943, clf__subsample=0.7630999564945671; total time=   0.5s\n",
+      "[CV] END clf__colsample_bylevel=0.5091891994585076, clf__colsample_bynode=0.8942779420776591, clf__colsample_bytree=0.9585526976941942, clf__gamma=0.09704478950707737, clf__learning_rate=0.001082794871840973, clf__max_depth=5, clf__reg_alpha=9.274914215839157, clf__reg_lambda=2.1283026903659943, clf__subsample=0.7630999564945671; total time=   0.4s\n",
+      "[CV] END clf__colsample_bylevel=0.5091891994585076, clf__colsample_bynode=0.8942779420776591, clf__colsample_bytree=0.9585526976941942, clf__gamma=0.09704478950707737, clf__learning_rate=0.001082794871840973, clf__max_depth=5, clf__reg_alpha=9.274914215839157, clf__reg_lambda=2.1283026903659943, clf__subsample=0.7630999564945671; total time=   0.4s\n",
+      "Fitting 3 folds for each of 1 candidates, totalling 3 fits\n",
+      "[CV] END clf__colsample_bylevel=0.9667866472759579, clf__colsample_bynode=0.756589540431827, clf__colsample_bytree=0.5183109110604756, clf__gamma=0.6563749139348486, clf__learning_rate=0.8020231136861821, clf__max_depth=4, clf__reg_alpha=1.7742271736420614, clf__reg_lambda=1.6170592289744992, clf__subsample=0.9587460864107861; total time=   0.4s\n",
+      "[CV] END clf__colsample_bylevel=0.9667866472759579, clf__colsample_bynode=0.756589540431827, clf__colsample_bytree=0.5183109110604756, clf__gamma=0.6563749139348486, clf__learning_rate=0.8020231136861821, clf__max_depth=4, clf__reg_alpha=1.7742271736420614, clf__reg_lambda=1.6170592289744992, clf__subsample=0.9587460864107861; total time=   0.4s\n",
+      "[CV] END clf__colsample_bylevel=0.9667866472759579, clf__colsample_bynode=0.756589540431827, clf__colsample_bytree=0.5183109110604756, clf__gamma=0.6563749139348486, clf__learning_rate=0.8020231136861821, clf__max_depth=4, clf__reg_alpha=1.7742271736420614, clf__reg_lambda=1.6170592289744992, clf__subsample=0.9587460864107861; total time=   0.4s\n",
+      "Fitting 3 folds for each of 1 candidates, totalling 3 fits\n",
+      "[CV] END clf__colsample_bylevel=0.5225167054873755, clf__colsample_bynode=0.7203413284241602, clf__colsample_bytree=1.0, clf__gamma=10.0, clf__learning_rate=0.03681144114853299, clf__max_depth=4, clf__reg_alpha=0.0, clf__reg_lambda=6.01677944462046, clf__subsample=0.5880016600496364; total time=   0.4s\n",
+      "[CV] END clf__colsample_bylevel=0.5225167054873755, clf__colsample_bynode=0.7203413284241602, clf__colsample_bytree=1.0, clf__gamma=10.0, clf__learning_rate=0.03681144114853299, clf__max_depth=4, clf__reg_alpha=0.0, clf__reg_lambda=6.01677944462046, clf__subsample=0.5880016600496364; total time=   0.4s\n",
+      "[CV] END clf__colsample_bylevel=0.5225167054873755, clf__colsample_bynode=0.7203413284241602, clf__colsample_bytree=1.0, clf__gamma=10.0, clf__learning_rate=0.03681144114853299, clf__max_depth=4, clf__reg_alpha=0.0, clf__reg_lambda=6.01677944462046, clf__subsample=0.5880016600496364; total time=   0.4s\n",
+      "Fitting 3 folds for each of 1 candidates, totalling 3 fits\n",
+      "[CV] END clf__colsample_bylevel=0.6166765512396893, clf__colsample_bynode=0.8475533219148963, clf__colsample_bytree=0.7210162320615964, clf__gamma=0.0, clf__learning_rate=0.001, clf__max_depth=2, clf__reg_alpha=0.0, clf__reg_lambda=2.3346893450449215, clf__subsample=0.6837672488303974; total time=   0.4s\n",
+      "[CV] END clf__colsample_bylevel=0.6166765512396893, clf__colsample_bynode=0.8475533219148963, clf__colsample_bytree=0.7210162320615964, clf__gamma=0.0, clf__learning_rate=0.001, clf__max_depth=2, clf__reg_alpha=0.0, clf__reg_lambda=2.3346893450449215, clf__subsample=0.6837672488303974; total time=   0.4s\n",
+      "[CV] END clf__colsample_bylevel=0.6166765512396893, clf__colsample_bynode=0.8475533219148963, clf__colsample_bytree=0.7210162320615964, clf__gamma=0.0, clf__learning_rate=0.001, clf__max_depth=2, clf__reg_alpha=0.0, clf__reg_lambda=2.3346893450449215, clf__subsample=0.6837672488303974; total time=   0.4s\n",
+      "Fitting 3 folds for each of 1 candidates, totalling 3 fits\n",
+      "[CV] END clf__colsample_bylevel=0.9406437118721191, clf__colsample_bynode=0.7481377937916189, clf__colsample_bytree=0.5076126608722743, clf__gamma=0.389296454396082, clf__learning_rate=0.021406691167827296, clf__max_depth=4, clf__reg_alpha=4.469298231686083, clf__reg_lambda=3.9552062576301483, clf__subsample=0.6130527840407582; total time=   0.5s\n",
+      "[CV] END clf__colsample_bylevel=0.9406437118721191, clf__colsample_bynode=0.7481377937916189, clf__colsample_bytree=0.5076126608722743, clf__gamma=0.389296454396082, clf__learning_rate=0.021406691167827296, clf__max_depth=4, clf__reg_alpha=4.469298231686083, clf__reg_lambda=3.9552062576301483, clf__subsample=0.6130527840407582; total time=   0.4s\n",
+      "[CV] END clf__colsample_bylevel=0.9406437118721191, clf__colsample_bynode=0.7481377937916189, clf__colsample_bytree=0.5076126608722743, clf__gamma=0.389296454396082, clf__learning_rate=0.021406691167827296, clf__max_depth=4, clf__reg_alpha=4.469298231686083, clf__reg_lambda=3.9552062576301483, clf__subsample=0.6130527840407582; total time=   0.4s\n",
+      "Fitting 3 folds for each of 1 candidates, totalling 3 fits\n",
+      "[CV] END clf__colsample_bylevel=0.5806962212230957, clf__colsample_bynode=0.7586902863302571, clf__colsample_bytree=0.7552310835375295, clf__gamma=10.0, clf__learning_rate=0.001, clf__max_depth=6, clf__reg_alpha=7.911043668944454, clf__reg_lambda=9.156553339386216, clf__subsample=0.7459268575731307; total time=   0.5s\n",
+      "[CV] END clf__colsample_bylevel=0.5806962212230957, clf__colsample_bynode=0.7586902863302571, clf__colsample_bytree=0.7552310835375295, clf__gamma=10.0, clf__learning_rate=0.001, clf__max_depth=6, clf__reg_alpha=7.911043668944454, clf__reg_lambda=9.156553339386216, clf__subsample=0.7459268575731307; total time=   0.6s\n",
+      "[CV] END clf__colsample_bylevel=0.5806962212230957, clf__colsample_bynode=0.7586902863302571, clf__colsample_bytree=0.7552310835375295, clf__gamma=10.0, clf__learning_rate=0.001, clf__max_depth=6, clf__reg_alpha=7.911043668944454, clf__reg_lambda=9.156553339386216, clf__subsample=0.7459268575731307; total time=   0.6s\n",
+      "Fitting 3 folds for each of 1 candidates, totalling 3 fits\n",
+      "[CV] END clf__colsample_bylevel=1.0, clf__colsample_bynode=0.5, clf__colsample_bytree=0.8467569097961967, clf__gamma=0.0, clf__learning_rate=0.10115118530494382, clf__max_depth=6, clf__reg_alpha=0.0, clf__reg_lambda=0.0, clf__subsample=0.5; total time=   0.8s\n",
+      "[CV] END clf__colsample_bylevel=1.0, clf__colsample_bynode=0.5, clf__colsample_bytree=0.8467569097961967, clf__gamma=0.0, clf__learning_rate=0.10115118530494382, clf__max_depth=6, clf__reg_alpha=0.0, clf__reg_lambda=0.0, clf__subsample=0.5; total time=   0.9s\n",
+      "[CV] END clf__colsample_bylevel=1.0, clf__colsample_bynode=0.5, clf__colsample_bytree=0.8467569097961967, clf__gamma=0.0, clf__learning_rate=0.10115118530494382, clf__max_depth=6, clf__reg_alpha=0.0, clf__reg_lambda=0.0, clf__subsample=0.5; total time=   0.9s\n",
+      "Fitting 3 folds for each of 1 candidates, totalling 3 fits\n",
+      "[CV] END clf__colsample_bylevel=1.0, clf__colsample_bynode=0.8802262489618233, clf__colsample_bytree=0.6471340731814139, clf__gamma=0.0, clf__learning_rate=0.11747225832482089, clf__max_depth=5, clf__reg_alpha=10.0, clf__reg_lambda=0.18422807726505983, clf__subsample=1.0; total time=   0.6s\n",
+      "[CV] END clf__colsample_bylevel=1.0, clf__colsample_bynode=0.8802262489618233, clf__colsample_bytree=0.6471340731814139, clf__gamma=0.0, clf__learning_rate=0.11747225832482089, clf__max_depth=5, clf__reg_alpha=10.0, clf__reg_lambda=0.18422807726505983, clf__subsample=1.0; total time=   0.7s\n",
+      "[CV] END clf__colsample_bylevel=1.0, clf__colsample_bynode=0.8802262489618233, clf__colsample_bytree=0.6471340731814139, clf__gamma=0.0, clf__learning_rate=0.11747225832482089, clf__max_depth=5, clf__reg_alpha=10.0, clf__reg_lambda=0.18422807726505983, clf__subsample=1.0; total time=   0.7s\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<style>#sk-container-id-2 {\n",
+       "  /* Definition of color scheme common for light and dark mode */\n",
+       "  --sklearn-color-text: #000;\n",
+       "  --sklearn-color-text-muted: #666;\n",
+       "  --sklearn-color-line: gray;\n",
+       "  /* Definition of color scheme for unfitted estimators */\n",
+       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
+       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
+       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
+       "  --sklearn-color-unfitted-level-3: chocolate;\n",
+       "  /* Definition of color scheme for fitted estimators */\n",
+       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
+       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
+       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
+       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
+       "\n",
+       "  /* Specific color for light theme */\n",
+       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
+       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
+       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
+       "  --sklearn-color-icon: #696969;\n",
+       "\n",
+       "  @media (prefers-color-scheme: dark) {\n",
+       "    /* Redefinition of color scheme for dark theme */\n",
+       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
+       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
+       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
+       "    --sklearn-color-icon: #878787;\n",
+       "  }\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 pre {\n",
+       "  padding: 0;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 input.sk-hidden--visually {\n",
+       "  border: 0;\n",
+       "  clip: rect(1px 1px 1px 1px);\n",
+       "  clip: rect(1px, 1px, 1px, 1px);\n",
+       "  height: 1px;\n",
+       "  margin: -1px;\n",
+       "  overflow: hidden;\n",
+       "  padding: 0;\n",
+       "  position: absolute;\n",
+       "  width: 1px;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-dashed-wrapped {\n",
+       "  border: 1px dashed var(--sklearn-color-line);\n",
+       "  margin: 0 0.4em 0.5em 0.4em;\n",
+       "  box-sizing: border-box;\n",
+       "  padding-bottom: 0.4em;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-container {\n",
+       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
+       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
+       "     so we also need the `!important` here to be able to override the\n",
+       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
+       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
+       "  display: inline-block !important;\n",
+       "  position: relative;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-text-repr-fallback {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       "div.sk-parallel-item,\n",
+       "div.sk-serial,\n",
+       "div.sk-item {\n",
+       "  /* draw centered vertical line to link estimators */\n",
+       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
+       "  background-size: 2px 100%;\n",
+       "  background-repeat: no-repeat;\n",
+       "  background-position: center center;\n",
+       "}\n",
+       "\n",
+       "/* Parallel-specific style estimator block */\n",
+       "\n",
+       "#sk-container-id-2 div.sk-parallel-item::after {\n",
+       "  content: \"\";\n",
+       "  width: 100%;\n",
+       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
+       "  flex-grow: 1;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-parallel {\n",
+       "  display: flex;\n",
+       "  align-items: stretch;\n",
+       "  justify-content: center;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  position: relative;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-parallel-item {\n",
+       "  display: flex;\n",
+       "  flex-direction: column;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-parallel-item:first-child::after {\n",
+       "  align-self: flex-end;\n",
+       "  width: 50%;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-parallel-item:last-child::after {\n",
+       "  align-self: flex-start;\n",
+       "  width: 50%;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-parallel-item:only-child::after {\n",
+       "  width: 0;\n",
+       "}\n",
+       "\n",
+       "/* Serial-specific style estimator block */\n",
+       "\n",
+       "#sk-container-id-2 div.sk-serial {\n",
+       "  display: flex;\n",
+       "  flex-direction: column;\n",
+       "  align-items: center;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  padding-right: 1em;\n",
+       "  padding-left: 1em;\n",
+       "}\n",
+       "\n",
+       "\n",
+       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
+       "clickable and can be expanded/collapsed.\n",
+       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
+       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
+       "*/\n",
+       "\n",
+       "/* Pipeline and ColumnTransformer style (default) */\n",
+       "\n",
+       "#sk-container-id-2 div.sk-toggleable {\n",
+       "  /* Default theme specific background. It is overwritten whether we have a\n",
+       "  specific estimator or a Pipeline/ColumnTransformer */\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "}\n",
+       "\n",
+       "/* Toggleable label */\n",
+       "#sk-container-id-2 label.sk-toggleable__label {\n",
+       "  cursor: pointer;\n",
+       "  display: flex;\n",
+       "  width: 100%;\n",
+       "  margin-bottom: 0;\n",
+       "  padding: 0.5em;\n",
+       "  box-sizing: border-box;\n",
+       "  text-align: center;\n",
+       "  align-items: start;\n",
+       "  justify-content: space-between;\n",
+       "  gap: 0.5em;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 label.sk-toggleable__label .caption {\n",
+       "  font-size: 0.6rem;\n",
+       "  font-weight: lighter;\n",
+       "  color: var(--sklearn-color-text-muted);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 label.sk-toggleable__label-arrow:before {\n",
+       "  /* Arrow on the left of the label */\n",
+       "  content: \"▸\";\n",
+       "  float: left;\n",
+       "  margin-right: 0.25em;\n",
+       "  color: var(--sklearn-color-icon);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 label.sk-toggleable__label-arrow:hover:before {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "}\n",
+       "\n",
+       "/* Toggleable content - dropdown */\n",
+       "\n",
+       "#sk-container-id-2 div.sk-toggleable__content {\n",
+       "  display: none;\n",
+       "  text-align: left;\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-toggleable__content.fitted {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-toggleable__content pre {\n",
+       "  margin: 0.2em;\n",
+       "  border-radius: 0.25em;\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-toggleable__content.fitted pre {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
+       "  /* Expand drop-down */\n",
+       "  display: block;\n",
+       "  width: 100%;\n",
+       "  overflow: visible;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
+       "  content: \"▾\";\n",
+       "}\n",
+       "\n",
+       "/* Pipeline/ColumnTransformer-specific style */\n",
+       "\n",
+       "#sk-container-id-2 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Estimator-specific style */\n",
+       "\n",
+       "/* Colorize estimator box */\n",
+       "#sk-container-id-2 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-label label.sk-toggleable__label,\n",
+       "#sk-container-id-2 div.sk-label label {\n",
+       "  /* The background is the default theme color */\n",
+       "  color: var(--sklearn-color-text-on-default-background);\n",
+       "}\n",
+       "\n",
+       "/* On hover, darken the color of the background */\n",
+       "#sk-container-id-2 div.sk-label:hover label.sk-toggleable__label {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Label box, darken color on hover, fitted */\n",
+       "#sk-container-id-2 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Estimator label */\n",
+       "\n",
+       "#sk-container-id-2 div.sk-label label {\n",
+       "  font-family: monospace;\n",
+       "  font-weight: bold;\n",
+       "  display: inline-block;\n",
+       "  line-height: 1.2em;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-label-container {\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       "/* Estimator-specific */\n",
+       "#sk-container-id-2 div.sk-estimator {\n",
+       "  font-family: monospace;\n",
+       "  border: 1px dotted var(--sklearn-color-border-box);\n",
+       "  border-radius: 0.25em;\n",
+       "  box-sizing: border-box;\n",
+       "  margin-bottom: 0.5em;\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-estimator.fitted {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "}\n",
+       "\n",
+       "/* on hover */\n",
+       "#sk-container-id-2 div.sk-estimator:hover {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 div.sk-estimator.fitted:hover {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
+       "\n",
+       "/* Common style for \"i\" and \"?\" */\n",
+       "\n",
+       ".sk-estimator-doc-link,\n",
+       "a:link.sk-estimator-doc-link,\n",
+       "a:visited.sk-estimator-doc-link {\n",
+       "  float: right;\n",
+       "  font-size: smaller;\n",
+       "  line-height: 1em;\n",
+       "  font-family: monospace;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  border-radius: 1em;\n",
+       "  height: 1em;\n",
+       "  width: 1em;\n",
+       "  text-decoration: none !important;\n",
+       "  margin-left: 0.5em;\n",
+       "  text-align: center;\n",
+       "  /* unfitted */\n",
+       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
+       "  color: var(--sklearn-color-unfitted-level-1);\n",
+       "}\n",
+       "\n",
+       ".sk-estimator-doc-link.fitted,\n",
+       "a:link.sk-estimator-doc-link.fitted,\n",
+       "a:visited.sk-estimator-doc-link.fitted {\n",
+       "  /* fitted */\n",
+       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
+       "  color: var(--sklearn-color-fitted-level-1);\n",
+       "}\n",
+       "\n",
+       "/* On hover */\n",
+       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
+       ".sk-estimator-doc-link:hover,\n",
+       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
+       ".sk-estimator-doc-link:hover {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
+       "  color: var(--sklearn-color-background);\n",
+       "  text-decoration: none;\n",
+       "}\n",
+       "\n",
+       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
+       ".sk-estimator-doc-link.fitted:hover,\n",
+       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
+       ".sk-estimator-doc-link.fitted:hover {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-3);\n",
+       "  color: var(--sklearn-color-background);\n",
+       "  text-decoration: none;\n",
+       "}\n",
+       "\n",
+       "/* Span, style for the box shown on hovering the info icon */\n",
+       ".sk-estimator-doc-link span {\n",
+       "  display: none;\n",
+       "  z-index: 9999;\n",
+       "  position: relative;\n",
+       "  font-weight: normal;\n",
+       "  right: .2ex;\n",
+       "  padding: .5ex;\n",
+       "  margin: .5ex;\n",
+       "  width: min-content;\n",
+       "  min-width: 20ex;\n",
+       "  max-width: 50ex;\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  box-shadow: 2pt 2pt 4pt #999;\n",
+       "  /* unfitted */\n",
+       "  background: var(--sklearn-color-unfitted-level-0);\n",
+       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
+       "}\n",
+       "\n",
+       ".sk-estimator-doc-link.fitted span {\n",
+       "  /* fitted */\n",
+       "  background: var(--sklearn-color-fitted-level-0);\n",
+       "  border: var(--sklearn-color-fitted-level-3);\n",
+       "}\n",
+       "\n",
+       ".sk-estimator-doc-link:hover span {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
+       "\n",
+       "#sk-container-id-2 a.estimator_doc_link {\n",
+       "  float: right;\n",
+       "  font-size: 1rem;\n",
+       "  line-height: 1em;\n",
+       "  font-family: monospace;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  border-radius: 1rem;\n",
+       "  height: 1rem;\n",
+       "  width: 1rem;\n",
+       "  text-decoration: none;\n",
+       "  /* unfitted */\n",
+       "  color: var(--sklearn-color-unfitted-level-1);\n",
+       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 a.estimator_doc_link.fitted {\n",
+       "  /* fitted */\n",
+       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
+       "  color: var(--sklearn-color-fitted-level-1);\n",
+       "}\n",
+       "\n",
+       "/* On hover */\n",
+       "#sk-container-id-2 a.estimator_doc_link:hover {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
+       "  color: var(--sklearn-color-background);\n",
+       "  text-decoration: none;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-2 a.estimator_doc_link.fitted:hover {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-3);\n",
+       "}\n",
+       "\n",
+       ".estimator-table summary {\n",
+       "    padding: .5rem;\n",
+       "    font-family: monospace;\n",
+       "    cursor: pointer;\n",
+       "}\n",
+       "\n",
+       ".estimator-table details[open] {\n",
+       "    padding-left: 0.1rem;\n",
+       "    padding-right: 0.1rem;\n",
+       "    padding-bottom: 0.3rem;\n",
+       "}\n",
+       "\n",
+       ".estimator-table .parameters-table {\n",
+       "    margin-left: auto !important;\n",
+       "    margin-right: auto !important;\n",
+       "}\n",
+       "\n",
+       ".estimator-table .parameters-table tr:nth-child(odd) {\n",
+       "    background-color: #fff;\n",
+       "}\n",
+       "\n",
+       ".estimator-table .parameters-table tr:nth-child(even) {\n",
+       "    background-color: #f6f6f6;\n",
+       "}\n",
+       "\n",
+       ".estimator-table .parameters-table tr:hover {\n",
+       "    background-color: #e0e0e0;\n",
+       "}\n",
+       "\n",
+       ".estimator-table table td {\n",
+       "    border: 1px solid rgba(106, 105, 104, 0.232);\n",
+       "}\n",
+       "\n",
+       ".user-set td {\n",
+       "    color:rgb(255, 94, 0);\n",
+       "    text-align: left;\n",
+       "}\n",
+       "\n",
+       ".user-set td.value pre {\n",
+       "    color:rgb(255, 94, 0) !important;\n",
+       "    background-color: transparent !important;\n",
+       "}\n",
+       "\n",
+       ".default td {\n",
+       "    color: black;\n",
+       "    text-align: left;\n",
+       "}\n",
+       "\n",
+       ".user-set td i,\n",
+       ".default td i {\n",
+       "    color: black;\n",
+       "}\n",
+       "\n",
+       ".copy-paste-icon {\n",
+       "    background-image: url(data:image/svg+xml;base64,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);\n",
+       "    background-repeat: no-repeat;\n",
+       "    background-size: 14px 14px;\n",
+       "    background-position: 0;\n",
+       "    display: inline-block;\n",
+       "    width: 14px;\n",
+       "    height: 14px;\n",
+       "    cursor: pointer;\n",
+       "}\n",
+       "</style><body><div id=\"sk-container-id-2\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>BayesSearchCV(cv=3,\n",
+       "              estimator=Pipeline(steps=[(&#x27;encoder&#x27;, TargetEncoder()),\n",
+       "                                        (&#x27;clf&#x27;,\n",
+       "                                         XGBClassifier(base_score=None,\n",
+       "                                                       booster=None,\n",
+       "                                                       callbacks=None,\n",
+       "                                                       colsample_bylevel=None,\n",
+       "                                                       colsample_bynode=None,\n",
+       "                                                       colsample_bytree=None,\n",
+       "                                                       device=None,\n",
+       "                                                       early_stopping_rounds=None,\n",
+       "                                                       enable_categorical=False,\n",
+       "                                                       eval_metric=None,\n",
+       "                                                       feature_types=None,\n",
+       "                                                       feature_weights=None,\n",
+       "                                                       gamma=None,\n",
+       "                                                       grow_policy=N...\n",
+       "                             &#x27;clf__learning_rate&#x27;: Real(low=0.001, high=1.0, prior=&#x27;log-uniform&#x27;, transform=&#x27;normalize&#x27;),\n",
+       "                             &#x27;clf__max_depth&#x27;: Integer(low=2, high=8, prior=&#x27;uniform&#x27;, transform=&#x27;normalize&#x27;),\n",
+       "                             &#x27;clf__reg_alpha&#x27;: Real(low=0.0, high=10.0, prior=&#x27;uniform&#x27;, transform=&#x27;normalize&#x27;),\n",
+       "                             &#x27;clf__reg_lambda&#x27;: Real(low=0.0, high=10.0, prior=&#x27;uniform&#x27;, transform=&#x27;normalize&#x27;),\n",
+       "                             &#x27;clf__subsample&#x27;: Real(low=0.5, high=1.0, prior=&#x27;uniform&#x27;, transform=&#x27;normalize&#x27;)},\n",
+       "              verbose=2)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-4\" type=\"checkbox\" ><label for=\"sk-estimator-id-4\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow\"><div><div>BayesSearchCV</div></div><div><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></div></label><div class=\"sk-toggleable__content fitted\" data-param-prefix=\"\">\n",
+       "        <div class=\"estimator-table\">\n",
+       "            <details>\n",
+       "                <summary>Parameters</summary>\n",
+       "                <table class=\"parameters-table\">\n",
+       "                  <tbody>\n",
+       "                    \n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('estimator',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">estimator&nbsp;</td>\n",
+       "            <td class=\"value\">Pipeline(step...=None, ...))])</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('search_spaces',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">search_spaces&nbsp;</td>\n",
+       "            <td class=\"value\">{&#x27;clf__colsample_bylevel&#x27;: Real(low=0.5,...m=&#x27;normalize&#x27;), &#x27;clf__colsample_bynode&#x27;: Real(low=0.5,...m=&#x27;normalize&#x27;), &#x27;clf__colsample_bytree&#x27;: Real(low=0.5,...m=&#x27;normalize&#x27;), &#x27;clf__gamma&#x27;: Real(low=0.0,...m=&#x27;normalize&#x27;), ...}</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('optimizer_kwargs',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">optimizer_kwargs&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('n_iter',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">n_iter&nbsp;</td>\n",
+       "            <td class=\"value\">30</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('scoring',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">scoring&nbsp;</td>\n",
+       "            <td class=\"value\">&#x27;roc_auc&#x27;</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('fit_params',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">fit_params&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('n_jobs',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">n_jobs&nbsp;</td>\n",
+       "            <td class=\"value\">-1</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('n_points',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">n_points&nbsp;</td>\n",
+       "            <td class=\"value\">1</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('iid',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">iid&nbsp;</td>\n",
+       "            <td class=\"value\">&#x27;deprecated&#x27;</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('refit',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">refit&nbsp;</td>\n",
+       "            <td class=\"value\">True</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('cv',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">cv&nbsp;</td>\n",
+       "            <td class=\"value\">3</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('verbose',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">verbose&nbsp;</td>\n",
+       "            <td class=\"value\">2</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('pre_dispatch',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">pre_dispatch&nbsp;</td>\n",
+       "            <td class=\"value\">&#x27;2*n_jobs&#x27;</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('random_state',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">random_state&nbsp;</td>\n",
+       "            <td class=\"value\">8</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('error_score',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">error_score&nbsp;</td>\n",
+       "            <td class=\"value\">&#x27;raise&#x27;</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('return_train_score',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">return_train_score&nbsp;</td>\n",
+       "            <td class=\"value\">True</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "                  </tbody>\n",
+       "                </table>\n",
+       "            </details>\n",
+       "        </div>\n",
+       "    </div></div></div><div class=\"sk-parallel\"><div class=\"sk-parallel-item\"><div class=\"sk-item\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-5\" type=\"checkbox\" ><label for=\"sk-estimator-id-5\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow\"><div><div>best_estimator_: Pipeline</div></div></label><div class=\"sk-toggleable__content fitted\" data-param-prefix=\"best_estimator___\"></div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-6\" type=\"checkbox\" ><label for=\"sk-estimator-id-6\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow\"><div><div>TargetEncoder</div></div></label><div class=\"sk-toggleable__content fitted\" data-param-prefix=\"best_estimator___encoder__\">\n",
+       "        <div class=\"estimator-table\">\n",
+       "            <details>\n",
+       "                <summary>Parameters</summary>\n",
+       "                <table class=\"parameters-table\">\n",
+       "                  <tbody>\n",
+       "                    \n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('verbose',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">verbose&nbsp;</td>\n",
+       "            <td class=\"value\">0</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('cols',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">cols&nbsp;</td>\n",
+       "            <td class=\"value\">[&#x27;job_type&#x27;, &#x27;marital&#x27;, ...]</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('drop_invariant',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">drop_invariant&nbsp;</td>\n",
+       "            <td class=\"value\">False</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('return_df',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">return_df&nbsp;</td>\n",
+       "            <td class=\"value\">True</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('handle_missing',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">handle_missing&nbsp;</td>\n",
+       "            <td class=\"value\">&#x27;value&#x27;</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('handle_unknown',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">handle_unknown&nbsp;</td>\n",
+       "            <td class=\"value\">&#x27;value&#x27;</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('min_samples_leaf',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">min_samples_leaf&nbsp;</td>\n",
+       "            <td class=\"value\">20</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('smoothing',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">smoothing&nbsp;</td>\n",
+       "            <td class=\"value\">10</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('hierarchy',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">hierarchy&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "                  </tbody>\n",
+       "                </table>\n",
+       "            </details>\n",
+       "        </div>\n",
+       "    </div></div></div><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-7\" type=\"checkbox\" ><label for=\"sk-estimator-id-7\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow\"><div><div>XGBClassifier</div></div><div><a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://xgboost.readthedocs.io/en/release_3.0.0/python/python_api.html#xgboost.XGBClassifier\">?<span>Documentation for XGBClassifier</span></a></div></label><div class=\"sk-toggleable__content fitted\" data-param-prefix=\"best_estimator___clf__\">\n",
+       "        <div class=\"estimator-table\">\n",
+       "            <details>\n",
+       "                <summary>Parameters</summary>\n",
+       "                <table class=\"parameters-table\">\n",
+       "                  <tbody>\n",
+       "                    \n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('objective',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">objective&nbsp;</td>\n",
+       "            <td class=\"value\">&#x27;binary:logistic&#x27;</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('base_score',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">base_score&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('booster',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">booster&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('callbacks',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">callbacks&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('colsample_bylevel',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">colsample_bylevel&nbsp;</td>\n",
+       "            <td class=\"value\">1.0</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('colsample_bynode',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">colsample_bynode&nbsp;</td>\n",
+       "            <td class=\"value\">0.8802262489618233</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('colsample_bytree',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">colsample_bytree&nbsp;</td>\n",
+       "            <td class=\"value\">0.6471340731814139</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('device',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">device&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('early_stopping_rounds',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">early_stopping_rounds&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('enable_categorical',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">enable_categorical&nbsp;</td>\n",
+       "            <td class=\"value\">False</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('eval_metric',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">eval_metric&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('feature_types',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">feature_types&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('feature_weights',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">feature_weights&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('gamma',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">gamma&nbsp;</td>\n",
+       "            <td class=\"value\">0.0</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('grow_policy',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">grow_policy&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('importance_type',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">importance_type&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('interaction_constraints',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">interaction_constraints&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('learning_rate',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">learning_rate&nbsp;</td>\n",
+       "            <td class=\"value\">0.11747225832482089</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('max_bin',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">max_bin&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('max_cat_threshold',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">max_cat_threshold&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('max_cat_to_onehot',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">max_cat_to_onehot&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('max_delta_step',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">max_delta_step&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('max_depth',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">max_depth&nbsp;</td>\n",
+       "            <td class=\"value\">5</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('max_leaves',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">max_leaves&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('min_child_weight',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">min_child_weight&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('missing',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">missing&nbsp;</td>\n",
+       "            <td class=\"value\">nan</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('monotone_constraints',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">monotone_constraints&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('multi_strategy',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">multi_strategy&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('n_estimators',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">n_estimators&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('n_jobs',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">n_jobs&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('num_parallel_tree',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">num_parallel_tree&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('random_state',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">random_state&nbsp;</td>\n",
+       "            <td class=\"value\">8</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('reg_alpha',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">reg_alpha&nbsp;</td>\n",
+       "            <td class=\"value\">10.0</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('reg_lambda',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">reg_lambda&nbsp;</td>\n",
+       "            <td class=\"value\">0.18422807726505983</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('sampling_method',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">sampling_method&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('scale_pos_weight',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">scale_pos_weight&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('subsample',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">subsample&nbsp;</td>\n",
+       "            <td class=\"value\">1.0</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('tree_method',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">tree_method&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('validate_parameters',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">validate_parameters&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('verbosity',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">verbosity&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "                  </tbody>\n",
+       "                </table>\n",
+       "            </details>\n",
+       "        </div>\n",
+       "    </div></div></div></div></div></div></div></div></div></div></div></div><script>function copyToClipboard(text, element) {\n",
+       "    // Get the parameter prefix from the closest toggleable content\n",
+       "    const toggleableContent = element.closest('.sk-toggleable__content');\n",
+       "    const paramPrefix = toggleableContent ? toggleableContent.dataset.paramPrefix : '';\n",
+       "    const fullParamName = paramPrefix ? `${paramPrefix}${text}` : text;\n",
+       "\n",
+       "    const originalStyle = element.style;\n",
+       "    const computedStyle = window.getComputedStyle(element);\n",
+       "    const originalWidth = computedStyle.width;\n",
+       "    const originalHTML = element.innerHTML.replace('Copied!', '');\n",
+       "\n",
+       "    navigator.clipboard.writeText(fullParamName)\n",
+       "        .then(() => {\n",
+       "            element.style.width = originalWidth;\n",
+       "            element.style.color = 'green';\n",
+       "            element.innerHTML = \"Copied!\";\n",
+       "\n",
+       "            setTimeout(() => {\n",
+       "                element.innerHTML = originalHTML;\n",
+       "                element.style = originalStyle;\n",
+       "            }, 2000);\n",
+       "        })\n",
+       "        .catch(err => {\n",
+       "            console.error('Failed to copy:', err);\n",
+       "            element.style.color = 'red';\n",
+       "            element.innerHTML = \"Failed!\";\n",
+       "            setTimeout(() => {\n",
+       "                element.innerHTML = originalHTML;\n",
+       "                element.style = originalStyle;\n",
+       "            }, 2000);\n",
+       "        });\n",
+       "    return false;\n",
+       "}\n",
+       "\n",
+       "document.querySelectorAll('.fa-regular.fa-copy').forEach(function(element) {\n",
+       "    const toggleableContent = element.closest('.sk-toggleable__content');\n",
+       "    const paramPrefix = toggleableContent ? toggleableContent.dataset.paramPrefix : '';\n",
+       "    const paramName = element.parentElement.nextElementSibling.textContent.trim();\n",
+       "    const fullParamName = paramPrefix ? `${paramPrefix}${paramName}` : paramName;\n",
+       "\n",
+       "    element.setAttribute('title', fullParamName);\n",
+       "});\n",
+       "</script></body>"
+      ],
+      "text/plain": [
+       "BayesSearchCV(cv=3,\n",
+       "              estimator=Pipeline(steps=[('encoder', TargetEncoder()),\n",
+       "                                        ('clf',\n",
+       "                                         XGBClassifier(base_score=None,\n",
+       "                                                       booster=None,\n",
+       "                                                       callbacks=None,\n",
+       "                                                       colsample_bylevel=None,\n",
+       "                                                       colsample_bynode=None,\n",
+       "                                                       colsample_bytree=None,\n",
+       "                                                       device=None,\n",
+       "                                                       early_stopping_rounds=None,\n",
+       "                                                       enable_categorical=False,\n",
+       "                                                       eval_metric=None,\n",
+       "                                                       feature_types=None,\n",
+       "                                                       feature_weights=None,\n",
+       "                                                       gamma=None,\n",
+       "                                                       grow_policy=N...\n",
+       "                             'clf__learning_rate': Real(low=0.001, high=1.0, prior='log-uniform', transform='normalize'),\n",
+       "                             'clf__max_depth': Integer(low=2, high=8, prior='uniform', transform='normalize'),\n",
+       "                             'clf__reg_alpha': Real(low=0.0, high=10.0, prior='uniform', transform='normalize'),\n",
+       "                             'clf__reg_lambda': Real(low=0.0, high=10.0, prior='uniform', transform='normalize'),\n",
+       "                             'clf__subsample': Real(low=0.5, high=1.0, prior='uniform', transform='normalize')},\n",
+       "              verbose=2)"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "opt.fit(X_train, y_train)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "780f95a5",
+   "metadata": {},
+   "source": [
+    "Evaluation and prediciton"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "82806480",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<style>#sk-container-id-3 {\n",
+       "  /* Definition of color scheme common for light and dark mode */\n",
+       "  --sklearn-color-text: #000;\n",
+       "  --sklearn-color-text-muted: #666;\n",
+       "  --sklearn-color-line: gray;\n",
+       "  /* Definition of color scheme for unfitted estimators */\n",
+       "  --sklearn-color-unfitted-level-0: #fff5e6;\n",
+       "  --sklearn-color-unfitted-level-1: #f6e4d2;\n",
+       "  --sklearn-color-unfitted-level-2: #ffe0b3;\n",
+       "  --sklearn-color-unfitted-level-3: chocolate;\n",
+       "  /* Definition of color scheme for fitted estimators */\n",
+       "  --sklearn-color-fitted-level-0: #f0f8ff;\n",
+       "  --sklearn-color-fitted-level-1: #d4ebff;\n",
+       "  --sklearn-color-fitted-level-2: #b3dbfd;\n",
+       "  --sklearn-color-fitted-level-3: cornflowerblue;\n",
+       "\n",
+       "  /* Specific color for light theme */\n",
+       "  --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
+       "  --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, white)));\n",
+       "  --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, black)));\n",
+       "  --sklearn-color-icon: #696969;\n",
+       "\n",
+       "  @media (prefers-color-scheme: dark) {\n",
+       "    /* Redefinition of color scheme for dark theme */\n",
+       "    --sklearn-color-text-on-default-background: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
+       "    --sklearn-color-background: var(--sg-background-color, var(--theme-background, var(--jp-layout-color0, #111)));\n",
+       "    --sklearn-color-border-box: var(--sg-text-color, var(--theme-code-foreground, var(--jp-content-font-color1, white)));\n",
+       "    --sklearn-color-icon: #878787;\n",
+       "  }\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 pre {\n",
+       "  padding: 0;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 input.sk-hidden--visually {\n",
+       "  border: 0;\n",
+       "  clip: rect(1px 1px 1px 1px);\n",
+       "  clip: rect(1px, 1px, 1px, 1px);\n",
+       "  height: 1px;\n",
+       "  margin: -1px;\n",
+       "  overflow: hidden;\n",
+       "  padding: 0;\n",
+       "  position: absolute;\n",
+       "  width: 1px;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-dashed-wrapped {\n",
+       "  border: 1px dashed var(--sklearn-color-line);\n",
+       "  margin: 0 0.4em 0.5em 0.4em;\n",
+       "  box-sizing: border-box;\n",
+       "  padding-bottom: 0.4em;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-container {\n",
+       "  /* jupyter's `normalize.less` sets `[hidden] { display: none; }`\n",
+       "     but bootstrap.min.css set `[hidden] { display: none !important; }`\n",
+       "     so we also need the `!important` here to be able to override the\n",
+       "     default hidden behavior on the sphinx rendered scikit-learn.org.\n",
+       "     See: https://github.com/scikit-learn/scikit-learn/issues/21755 */\n",
+       "  display: inline-block !important;\n",
+       "  position: relative;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-text-repr-fallback {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       "div.sk-parallel-item,\n",
+       "div.sk-serial,\n",
+       "div.sk-item {\n",
+       "  /* draw centered vertical line to link estimators */\n",
+       "  background-image: linear-gradient(var(--sklearn-color-text-on-default-background), var(--sklearn-color-text-on-default-background));\n",
+       "  background-size: 2px 100%;\n",
+       "  background-repeat: no-repeat;\n",
+       "  background-position: center center;\n",
+       "}\n",
+       "\n",
+       "/* Parallel-specific style estimator block */\n",
+       "\n",
+       "#sk-container-id-3 div.sk-parallel-item::after {\n",
+       "  content: \"\";\n",
+       "  width: 100%;\n",
+       "  border-bottom: 2px solid var(--sklearn-color-text-on-default-background);\n",
+       "  flex-grow: 1;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-parallel {\n",
+       "  display: flex;\n",
+       "  align-items: stretch;\n",
+       "  justify-content: center;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  position: relative;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-parallel-item {\n",
+       "  display: flex;\n",
+       "  flex-direction: column;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-parallel-item:first-child::after {\n",
+       "  align-self: flex-end;\n",
+       "  width: 50%;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-parallel-item:last-child::after {\n",
+       "  align-self: flex-start;\n",
+       "  width: 50%;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-parallel-item:only-child::after {\n",
+       "  width: 0;\n",
+       "}\n",
+       "\n",
+       "/* Serial-specific style estimator block */\n",
+       "\n",
+       "#sk-container-id-3 div.sk-serial {\n",
+       "  display: flex;\n",
+       "  flex-direction: column;\n",
+       "  align-items: center;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  padding-right: 1em;\n",
+       "  padding-left: 1em;\n",
+       "}\n",
+       "\n",
+       "\n",
+       "/* Toggleable style: style used for estimator/Pipeline/ColumnTransformer box that is\n",
+       "clickable and can be expanded/collapsed.\n",
+       "- Pipeline and ColumnTransformer use this feature and define the default style\n",
+       "- Estimators will overwrite some part of the style using the `sk-estimator` class\n",
+       "*/\n",
+       "\n",
+       "/* Pipeline and ColumnTransformer style (default) */\n",
+       "\n",
+       "#sk-container-id-3 div.sk-toggleable {\n",
+       "  /* Default theme specific background. It is overwritten whether we have a\n",
+       "  specific estimator or a Pipeline/ColumnTransformer */\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "}\n",
+       "\n",
+       "/* Toggleable label */\n",
+       "#sk-container-id-3 label.sk-toggleable__label {\n",
+       "  cursor: pointer;\n",
+       "  display: flex;\n",
+       "  width: 100%;\n",
+       "  margin-bottom: 0;\n",
+       "  padding: 0.5em;\n",
+       "  box-sizing: border-box;\n",
+       "  text-align: center;\n",
+       "  align-items: start;\n",
+       "  justify-content: space-between;\n",
+       "  gap: 0.5em;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 label.sk-toggleable__label .caption {\n",
+       "  font-size: 0.6rem;\n",
+       "  font-weight: lighter;\n",
+       "  color: var(--sklearn-color-text-muted);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 label.sk-toggleable__label-arrow:before {\n",
+       "  /* Arrow on the left of the label */\n",
+       "  content: \"▸\";\n",
+       "  float: left;\n",
+       "  margin-right: 0.25em;\n",
+       "  color: var(--sklearn-color-icon);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 label.sk-toggleable__label-arrow:hover:before {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "}\n",
+       "\n",
+       "/* Toggleable content - dropdown */\n",
+       "\n",
+       "#sk-container-id-3 div.sk-toggleable__content {\n",
+       "  display: none;\n",
+       "  text-align: left;\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-toggleable__content.fitted {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-toggleable__content pre {\n",
+       "  margin: 0.2em;\n",
+       "  border-radius: 0.25em;\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-toggleable__content.fitted pre {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 input.sk-toggleable__control:checked~div.sk-toggleable__content {\n",
+       "  /* Expand drop-down */\n",
+       "  display: block;\n",
+       "  width: 100%;\n",
+       "  overflow: visible;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {\n",
+       "  content: \"▾\";\n",
+       "}\n",
+       "\n",
+       "/* Pipeline/ColumnTransformer-specific style */\n",
+       "\n",
+       "#sk-container-id-3 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-label.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Estimator-specific style */\n",
+       "\n",
+       "/* Colorize estimator box */\n",
+       "#sk-container-id-3 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-estimator.fitted input.sk-toggleable__control:checked~label.sk-toggleable__label {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-label label.sk-toggleable__label,\n",
+       "#sk-container-id-3 div.sk-label label {\n",
+       "  /* The background is the default theme color */\n",
+       "  color: var(--sklearn-color-text-on-default-background);\n",
+       "}\n",
+       "\n",
+       "/* On hover, darken the color of the background */\n",
+       "#sk-container-id-3 div.sk-label:hover label.sk-toggleable__label {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Label box, darken color on hover, fitted */\n",
+       "#sk-container-id-3 div.sk-label.fitted:hover label.sk-toggleable__label.fitted {\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Estimator label */\n",
+       "\n",
+       "#sk-container-id-3 div.sk-label label {\n",
+       "  font-family: monospace;\n",
+       "  font-weight: bold;\n",
+       "  display: inline-block;\n",
+       "  line-height: 1.2em;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-label-container {\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       "/* Estimator-specific */\n",
+       "#sk-container-id-3 div.sk-estimator {\n",
+       "  font-family: monospace;\n",
+       "  border: 1px dotted var(--sklearn-color-border-box);\n",
+       "  border-radius: 0.25em;\n",
+       "  box-sizing: border-box;\n",
+       "  margin-bottom: 0.5em;\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-0);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-estimator.fitted {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-0);\n",
+       "}\n",
+       "\n",
+       "/* on hover */\n",
+       "#sk-container-id-3 div.sk-estimator:hover {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-2);\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 div.sk-estimator.fitted:hover {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-2);\n",
+       "}\n",
+       "\n",
+       "/* Specification for estimator info (e.g. \"i\" and \"?\") */\n",
+       "\n",
+       "/* Common style for \"i\" and \"?\" */\n",
+       "\n",
+       ".sk-estimator-doc-link,\n",
+       "a:link.sk-estimator-doc-link,\n",
+       "a:visited.sk-estimator-doc-link {\n",
+       "  float: right;\n",
+       "  font-size: smaller;\n",
+       "  line-height: 1em;\n",
+       "  font-family: monospace;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  border-radius: 1em;\n",
+       "  height: 1em;\n",
+       "  width: 1em;\n",
+       "  text-decoration: none !important;\n",
+       "  margin-left: 0.5em;\n",
+       "  text-align: center;\n",
+       "  /* unfitted */\n",
+       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
+       "  color: var(--sklearn-color-unfitted-level-1);\n",
+       "}\n",
+       "\n",
+       ".sk-estimator-doc-link.fitted,\n",
+       "a:link.sk-estimator-doc-link.fitted,\n",
+       "a:visited.sk-estimator-doc-link.fitted {\n",
+       "  /* fitted */\n",
+       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
+       "  color: var(--sklearn-color-fitted-level-1);\n",
+       "}\n",
+       "\n",
+       "/* On hover */\n",
+       "div.sk-estimator:hover .sk-estimator-doc-link:hover,\n",
+       ".sk-estimator-doc-link:hover,\n",
+       "div.sk-label-container:hover .sk-estimator-doc-link:hover,\n",
+       ".sk-estimator-doc-link:hover {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
+       "  color: var(--sklearn-color-background);\n",
+       "  text-decoration: none;\n",
+       "}\n",
+       "\n",
+       "div.sk-estimator.fitted:hover .sk-estimator-doc-link.fitted:hover,\n",
+       ".sk-estimator-doc-link.fitted:hover,\n",
+       "div.sk-label-container:hover .sk-estimator-doc-link.fitted:hover,\n",
+       ".sk-estimator-doc-link.fitted:hover {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-3);\n",
+       "  color: var(--sklearn-color-background);\n",
+       "  text-decoration: none;\n",
+       "}\n",
+       "\n",
+       "/* Span, style for the box shown on hovering the info icon */\n",
+       ".sk-estimator-doc-link span {\n",
+       "  display: none;\n",
+       "  z-index: 9999;\n",
+       "  position: relative;\n",
+       "  font-weight: normal;\n",
+       "  right: .2ex;\n",
+       "  padding: .5ex;\n",
+       "  margin: .5ex;\n",
+       "  width: min-content;\n",
+       "  min-width: 20ex;\n",
+       "  max-width: 50ex;\n",
+       "  color: var(--sklearn-color-text);\n",
+       "  box-shadow: 2pt 2pt 4pt #999;\n",
+       "  /* unfitted */\n",
+       "  background: var(--sklearn-color-unfitted-level-0);\n",
+       "  border: .5pt solid var(--sklearn-color-unfitted-level-3);\n",
+       "}\n",
+       "\n",
+       ".sk-estimator-doc-link.fitted span {\n",
+       "  /* fitted */\n",
+       "  background: var(--sklearn-color-fitted-level-0);\n",
+       "  border: var(--sklearn-color-fitted-level-3);\n",
+       "}\n",
+       "\n",
+       ".sk-estimator-doc-link:hover span {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       "/* \"?\"-specific style due to the `<a>` HTML tag */\n",
+       "\n",
+       "#sk-container-id-3 a.estimator_doc_link {\n",
+       "  float: right;\n",
+       "  font-size: 1rem;\n",
+       "  line-height: 1em;\n",
+       "  font-family: monospace;\n",
+       "  background-color: var(--sklearn-color-background);\n",
+       "  border-radius: 1rem;\n",
+       "  height: 1rem;\n",
+       "  width: 1rem;\n",
+       "  text-decoration: none;\n",
+       "  /* unfitted */\n",
+       "  color: var(--sklearn-color-unfitted-level-1);\n",
+       "  border: var(--sklearn-color-unfitted-level-1) 1pt solid;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 a.estimator_doc_link.fitted {\n",
+       "  /* fitted */\n",
+       "  border: var(--sklearn-color-fitted-level-1) 1pt solid;\n",
+       "  color: var(--sklearn-color-fitted-level-1);\n",
+       "}\n",
+       "\n",
+       "/* On hover */\n",
+       "#sk-container-id-3 a.estimator_doc_link:hover {\n",
+       "  /* unfitted */\n",
+       "  background-color: var(--sklearn-color-unfitted-level-3);\n",
+       "  color: var(--sklearn-color-background);\n",
+       "  text-decoration: none;\n",
+       "}\n",
+       "\n",
+       "#sk-container-id-3 a.estimator_doc_link.fitted:hover {\n",
+       "  /* fitted */\n",
+       "  background-color: var(--sklearn-color-fitted-level-3);\n",
+       "}\n",
+       "\n",
+       ".estimator-table summary {\n",
+       "    padding: .5rem;\n",
+       "    font-family: monospace;\n",
+       "    cursor: pointer;\n",
+       "}\n",
+       "\n",
+       ".estimator-table details[open] {\n",
+       "    padding-left: 0.1rem;\n",
+       "    padding-right: 0.1rem;\n",
+       "    padding-bottom: 0.3rem;\n",
+       "}\n",
+       "\n",
+       ".estimator-table .parameters-table {\n",
+       "    margin-left: auto !important;\n",
+       "    margin-right: auto !important;\n",
+       "}\n",
+       "\n",
+       ".estimator-table .parameters-table tr:nth-child(odd) {\n",
+       "    background-color: #fff;\n",
+       "}\n",
+       "\n",
+       ".estimator-table .parameters-table tr:nth-child(even) {\n",
+       "    background-color: #f6f6f6;\n",
+       "}\n",
+       "\n",
+       ".estimator-table .parameters-table tr:hover {\n",
+       "    background-color: #e0e0e0;\n",
+       "}\n",
+       "\n",
+       ".estimator-table table td {\n",
+       "    border: 1px solid rgba(106, 105, 104, 0.232);\n",
+       "}\n",
+       "\n",
+       ".user-set td {\n",
+       "    color:rgb(255, 94, 0);\n",
+       "    text-align: left;\n",
+       "}\n",
+       "\n",
+       ".user-set td.value pre {\n",
+       "    color:rgb(255, 94, 0) !important;\n",
+       "    background-color: transparent !important;\n",
+       "}\n",
+       "\n",
+       ".default td {\n",
+       "    color: black;\n",
+       "    text-align: left;\n",
+       "}\n",
+       "\n",
+       ".user-set td i,\n",
+       ".default td i {\n",
+       "    color: black;\n",
+       "}\n",
+       "\n",
+       ".copy-paste-icon {\n",
+       "    background-image: url(data:image/svg+xml;base64,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);\n",
+       "    background-repeat: no-repeat;\n",
+       "    background-size: 14px 14px;\n",
+       "    background-position: 0;\n",
+       "    display: inline-block;\n",
+       "    width: 14px;\n",
+       "    height: 14px;\n",
+       "    cursor: pointer;\n",
+       "}\n",
+       "</style><body><div id=\"sk-container-id-3\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>Pipeline(steps=[(&#x27;encoder&#x27;,\n",
+       "                 TargetEncoder(cols=[&#x27;job_type&#x27;, &#x27;marital&#x27;, &#x27;education&#x27;,\n",
+       "                                     &#x27;default_status&#x27;, &#x27;housing_loan_status&#x27;,\n",
+       "                                     &#x27;personal_loan_status&#x27;, &#x27;contact_type&#x27;,\n",
+       "                                     &#x27;contact_month&#x27;, &#x27;contact_day_of_week&#x27;,\n",
+       "                                     &#x27;previous_outcome&#x27;])),\n",
+       "                (&#x27;clf&#x27;,\n",
+       "                 XGBClassifier(base_score=None, booster=None, callbacks=None,\n",
+       "                               colsample_bylevel=1.0,\n",
+       "                               colsample_bynode=0.8802262489618233,\n",
+       "                               colsample_...\n",
+       "                               gamma=0.0, grow_policy=None,\n",
+       "                               importance_type=None,\n",
+       "                               interaction_constraints=None,\n",
+       "                               learning_rate=0.11747225832482089, max_bin=None,\n",
+       "                               max_cat_threshold=None, max_cat_to_onehot=None,\n",
+       "                               max_delta_step=None, max_depth=5,\n",
+       "                               max_leaves=None, min_child_weight=None,\n",
+       "                               missing=nan, monotone_constraints=None,\n",
+       "                               multi_strategy=None, n_estimators=None,\n",
+       "                               n_jobs=None, num_parallel_tree=None, ...))])</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item sk-dashed-wrapped\"><div class=\"sk-label-container\"><div class=\"sk-label fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-8\" type=\"checkbox\" ><label for=\"sk-estimator-id-8\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow\"><div><div>Pipeline</div></div><div><a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://scikit-learn.org/1.7/modules/generated/sklearn.pipeline.Pipeline.html\">?<span>Documentation for Pipeline</span></a><span class=\"sk-estimator-doc-link fitted\">i<span>Fitted</span></span></div></label><div class=\"sk-toggleable__content fitted\" data-param-prefix=\"\">\n",
+       "        <div class=\"estimator-table\">\n",
+       "            <details>\n",
+       "                <summary>Parameters</summary>\n",
+       "                <table class=\"parameters-table\">\n",
+       "                  <tbody>\n",
+       "                    \n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('steps',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">steps&nbsp;</td>\n",
+       "            <td class=\"value\">[(&#x27;encoder&#x27;, ...), (&#x27;clf&#x27;, ...)]</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('transform_input',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">transform_input&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('memory',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">memory&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('verbose',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">verbose&nbsp;</td>\n",
+       "            <td class=\"value\">False</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "                  </tbody>\n",
+       "                </table>\n",
+       "            </details>\n",
+       "        </div>\n",
+       "    </div></div></div><div class=\"sk-serial\"><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-9\" type=\"checkbox\" ><label for=\"sk-estimator-id-9\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow\"><div><div>TargetEncoder</div></div></label><div class=\"sk-toggleable__content fitted\" data-param-prefix=\"encoder__\">\n",
+       "        <div class=\"estimator-table\">\n",
+       "            <details>\n",
+       "                <summary>Parameters</summary>\n",
+       "                <table class=\"parameters-table\">\n",
+       "                  <tbody>\n",
+       "                    \n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('verbose',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">verbose&nbsp;</td>\n",
+       "            <td class=\"value\">0</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('cols',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">cols&nbsp;</td>\n",
+       "            <td class=\"value\">[&#x27;job_type&#x27;, &#x27;marital&#x27;, ...]</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('drop_invariant',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">drop_invariant&nbsp;</td>\n",
+       "            <td class=\"value\">False</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('return_df',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">return_df&nbsp;</td>\n",
+       "            <td class=\"value\">True</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('handle_missing',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">handle_missing&nbsp;</td>\n",
+       "            <td class=\"value\">&#x27;value&#x27;</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('handle_unknown',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">handle_unknown&nbsp;</td>\n",
+       "            <td class=\"value\">&#x27;value&#x27;</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('min_samples_leaf',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">min_samples_leaf&nbsp;</td>\n",
+       "            <td class=\"value\">20</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('smoothing',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">smoothing&nbsp;</td>\n",
+       "            <td class=\"value\">10</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('hierarchy',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">hierarchy&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "                  </tbody>\n",
+       "                </table>\n",
+       "            </details>\n",
+       "        </div>\n",
+       "    </div></div></div><div class=\"sk-item\"><div class=\"sk-estimator fitted sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-10\" type=\"checkbox\" ><label for=\"sk-estimator-id-10\" class=\"sk-toggleable__label fitted sk-toggleable__label-arrow\"><div><div>XGBClassifier</div></div><div><a class=\"sk-estimator-doc-link fitted\" rel=\"noreferrer\" target=\"_blank\" href=\"https://xgboost.readthedocs.io/en/release_3.0.0/python/python_api.html#xgboost.XGBClassifier\">?<span>Documentation for XGBClassifier</span></a></div></label><div class=\"sk-toggleable__content fitted\" data-param-prefix=\"clf__\">\n",
+       "        <div class=\"estimator-table\">\n",
+       "            <details>\n",
+       "                <summary>Parameters</summary>\n",
+       "                <table class=\"parameters-table\">\n",
+       "                  <tbody>\n",
+       "                    \n",
+       "        <tr class=\"default\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('objective',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">objective&nbsp;</td>\n",
+       "            <td class=\"value\">&#x27;binary:logistic&#x27;</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('base_score',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">base_score&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('booster',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">booster&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('callbacks',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">callbacks&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('colsample_bylevel',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">colsample_bylevel&nbsp;</td>\n",
+       "            <td class=\"value\">1.0</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('colsample_bynode',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">colsample_bynode&nbsp;</td>\n",
+       "            <td class=\"value\">0.8802262489618233</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('colsample_bytree',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">colsample_bytree&nbsp;</td>\n",
+       "            <td class=\"value\">0.6471340731814139</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('device',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">device&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('early_stopping_rounds',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">early_stopping_rounds&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('enable_categorical',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">enable_categorical&nbsp;</td>\n",
+       "            <td class=\"value\">False</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('eval_metric',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">eval_metric&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('feature_types',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">feature_types&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('feature_weights',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">feature_weights&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('gamma',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">gamma&nbsp;</td>\n",
+       "            <td class=\"value\">0.0</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('grow_policy',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">grow_policy&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('importance_type',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">importance_type&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('interaction_constraints',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">interaction_constraints&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('learning_rate',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">learning_rate&nbsp;</td>\n",
+       "            <td class=\"value\">0.11747225832482089</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('max_bin',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">max_bin&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('max_cat_threshold',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">max_cat_threshold&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('max_cat_to_onehot',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">max_cat_to_onehot&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('max_delta_step',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">max_delta_step&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('max_depth',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">max_depth&nbsp;</td>\n",
+       "            <td class=\"value\">5</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('max_leaves',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">max_leaves&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('min_child_weight',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">min_child_weight&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('missing',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">missing&nbsp;</td>\n",
+       "            <td class=\"value\">nan</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('monotone_constraints',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">monotone_constraints&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('multi_strategy',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">multi_strategy&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('n_estimators',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">n_estimators&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('n_jobs',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">n_jobs&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('num_parallel_tree',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">num_parallel_tree&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('random_state',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">random_state&nbsp;</td>\n",
+       "            <td class=\"value\">8</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('reg_alpha',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">reg_alpha&nbsp;</td>\n",
+       "            <td class=\"value\">10.0</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('reg_lambda',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">reg_lambda&nbsp;</td>\n",
+       "            <td class=\"value\">0.18422807726505983</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('sampling_method',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">sampling_method&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('scale_pos_weight',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">scale_pos_weight&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('subsample',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">subsample&nbsp;</td>\n",
+       "            <td class=\"value\">1.0</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('tree_method',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">tree_method&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('validate_parameters',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">validate_parameters&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "\n",
+       "        <tr class=\"user-set\">\n",
+       "            <td><i class=\"copy-paste-icon\"\n",
+       "                 onclick=\"copyToClipboard('verbosity',\n",
+       "                          this.parentElement.nextElementSibling)\"\n",
+       "            ></i></td>\n",
+       "            <td class=\"param\">verbosity&nbsp;</td>\n",
+       "            <td class=\"value\">None</td>\n",
+       "        </tr>\n",
+       "    \n",
+       "                  </tbody>\n",
+       "                </table>\n",
+       "            </details>\n",
+       "        </div>\n",
+       "    </div></div></div></div></div></div></div><script>function copyToClipboard(text, element) {\n",
+       "    // Get the parameter prefix from the closest toggleable content\n",
+       "    const toggleableContent = element.closest('.sk-toggleable__content');\n",
+       "    const paramPrefix = toggleableContent ? toggleableContent.dataset.paramPrefix : '';\n",
+       "    const fullParamName = paramPrefix ? `${paramPrefix}${text}` : text;\n",
+       "\n",
+       "    const originalStyle = element.style;\n",
+       "    const computedStyle = window.getComputedStyle(element);\n",
+       "    const originalWidth = computedStyle.width;\n",
+       "    const originalHTML = element.innerHTML.replace('Copied!', '');\n",
+       "\n",
+       "    navigator.clipboard.writeText(fullParamName)\n",
+       "        .then(() => {\n",
+       "            element.style.width = originalWidth;\n",
+       "            element.style.color = 'green';\n",
+       "            element.innerHTML = \"Copied!\";\n",
+       "\n",
+       "            setTimeout(() => {\n",
+       "                element.innerHTML = originalHTML;\n",
+       "                element.style = originalStyle;\n",
+       "            }, 2000);\n",
+       "        })\n",
+       "        .catch(err => {\n",
+       "            console.error('Failed to copy:', err);\n",
+       "            element.style.color = 'red';\n",
+       "            element.innerHTML = \"Failed!\";\n",
+       "            setTimeout(() => {\n",
+       "                element.innerHTML = originalHTML;\n",
+       "                element.style = originalStyle;\n",
+       "            }, 2000);\n",
+       "        });\n",
+       "    return false;\n",
+       "}\n",
+       "\n",
+       "document.querySelectorAll('.fa-regular.fa-copy').forEach(function(element) {\n",
+       "    const toggleableContent = element.closest('.sk-toggleable__content');\n",
+       "    const paramPrefix = toggleableContent ? toggleableContent.dataset.paramPrefix : '';\n",
+       "    const paramName = element.parentElement.nextElementSibling.textContent.trim();\n",
+       "    const fullParamName = paramPrefix ? `${paramPrefix}${paramName}` : paramName;\n",
+       "\n",
+       "    element.setAttribute('title', fullParamName);\n",
+       "});\n",
+       "</script></body>"
+      ],
+      "text/plain": [
+       "Pipeline(steps=[('encoder',\n",
+       "                 TargetEncoder(cols=['job_type', 'marital', 'education',\n",
+       "                                     'default_status', 'housing_loan_status',\n",
+       "                                     'personal_loan_status', 'contact_type',\n",
+       "                                     'contact_month', 'contact_day_of_week',\n",
+       "                                     'previous_outcome'])),\n",
+       "                ('clf',\n",
+       "                 XGBClassifier(base_score=None, booster=None, callbacks=None,\n",
+       "                               colsample_bylevel=1.0,\n",
+       "                               colsample_bynode=0.8802262489618233,\n",
+       "                               colsample_...\n",
+       "                               gamma=0.0, grow_policy=None,\n",
+       "                               importance_type=None,\n",
+       "                               interaction_constraints=None,\n",
+       "                               learning_rate=0.11747225832482089, max_bin=None,\n",
+       "                               max_cat_threshold=None, max_cat_to_onehot=None,\n",
+       "                               max_delta_step=None, max_depth=5,\n",
+       "                               max_leaves=None, min_child_weight=None,\n",
+       "                               missing=nan, monotone_constraints=None,\n",
+       "                               multi_strategy=None, n_estimators=None,\n",
+       "                               n_jobs=None, num_parallel_tree=None, ...))])"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "opt.best_estimator_"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "84d0865a",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "np.float64(0.7760446966697848)"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "opt.best_score_"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "060795a0",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0.7609064484773256"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "opt.score(X_test, y_test)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "1bc301ca",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([0, 0, 0, ..., 0, 0, 0], shape=(8238,))"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "opt.predict(X_test)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "c4559bab",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([[0.9707873 , 0.02921269],\n",
+       "       [0.909715  , 0.09028501],\n",
+       "       [0.8761    , 0.12390002],\n",
+       "       ...,\n",
+       "       [0.93365276, 0.06634723],\n",
+       "       [0.8354016 , 0.16459839],\n",
+       "       [0.93391794, 0.06608208]], shape=(8238, 2), dtype=float32)"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "opt.predict_proba(X_test)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "bf4bdbb6",
+   "metadata": {},
+   "source": [
+    "Measuring Feature importance"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "809e3b5c",
+   "metadata": {},
+   "source": [
+    "It plots the factors that contriubuted most."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "9b69fc8c",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<Axes: title={'center': 'Feature importance'}, xlabel='Importance score', ylabel='Features'>"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "from xgboost import plot_importance\n",
+    "\n",
+    "opt.best_estimator_.steps\n",
+    "xgboost_step = opt.best_estimator_.steps[1]\n",
+    "xgboost_model = xgboost_step[1]\n",
+    "plot_importance(xgboost_model)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": ".venv",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.18"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/aes.py b/python/aes.py
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diff --git a/aks prime test.py b/python/aks prime test.py
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diff --git a/balanced_paranthesis.py b/python/balanced_paranthesis.py
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diff --git a/bellmenford.py b/python/bellmenford.py
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diff --git a/binary_search.py b/python/binary_search.py
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diff --git a/bmi-calculator.py b/python/bmi-calculator.py
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diff --git a/bmi.py b/python/bmi.py
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diff --git a/bubble_sort.py b/python/bubble_sort.py
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diff --git a/calculator.py b/python/calculator.py
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diff --git a/clock.py b/python/clock.py
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diff --git a/count_inversions.py b/python/count_inversions.py
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diff --git a/cycleSort.py b/python/cycleSort.py
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diff --git a/cycle_detection_linked_list.py b/python/cycle_detection_linked_list.py
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diff --git a/diameter_Btree.py b/python/diameter_Btree.py
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rename to python/diameter_Btree.py
diff --git a/dijkstra.py b/python/dijkstra.py
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diff --git a/fraction.py b/python/fraction.py
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diff --git a/hybrid_sort.py b/python/hybrid_sort.py
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diff --git a/insertion-sort.py b/python/insertion-sort.py
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diff --git a/knapsack.py b/python/knapsack.py
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diff --git a/kruskal.py b/python/kruskal.py
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diff --git a/livecliterminal.py b/python/livecliterminal.py
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diff --git a/mandelbrot_Set.py b/python/mandelbrot_Set.py
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diff --git a/matching_paren.py b/python/matching_paren.py
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rename to python/matching_paren.py
diff --git a/matplotlib_graphs.ipynb b/python/matplotlib_graphs.ipynb
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diff --git a/matrixMultiply.py b/python/matrixMultiply.py
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rename to python/matrixMultiply.py
diff --git a/merge_sort.py b/python/merge_sort.py
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diff --git a/min_in_sorted_&_rotated_array.py b/python/min_in_sorted_&_rotated_array.py
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rename from min_in_sorted_&_rotated_array.py
rename to python/min_in_sorted_&_rotated_array.py
diff --git a/mirror_matrix.ipynb b/python/mirror_matrix.ipynb
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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "fd34a325",
+   "metadata": {},
+   "source": [
+    "# A file for functions  of scikit-learn(sklearn) library\n",
+    "(Note: These are all simple implementations)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "7d404571",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd # to handle dataframes\n",
+    "import sklearn as skl\n",
+    "from sklearn.model_selection import train_test_split\n",
+    "from sklearn.preprocessing import StandardScaler\n",
+    "from sklearn.linear_model import LogisticRegression\n",
+    "from sklearn.metrics import classification_report , accuracy_score\n",
+    "from sklearn.neighbors import KNeighborsClassifier\n",
+    "from sklearn.svm import SVC\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "cf06a9a6",
+   "metadata": {},
+   "source": [
+    "Reading the csv"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "10a208c2",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>fLength</th>\n",
+       "      <th>fWidth</th>\n",
+       "      <th>fSize</th>\n",
+       "      <th>fConc</th>\n",
+       "      <th>fConc1</th>\n",
+       "      <th>fAsym</th>\n",
+       "      <th>fM3Long</th>\n",
+       "      <th>fM3Trans</th>\n",
+       "      <th>fAlpha</th>\n",
+       "      <th>fDist</th>\n",
+       "      <th>class</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>28.7967</td>\n",
+       "      <td>16.0021</td>\n",
+       "      <td>2.6449</td>\n",
+       "      <td>0.3918</td>\n",
+       "      <td>0.1982</td>\n",
+       "      <td>27.7004</td>\n",
+       "      <td>22.0110</td>\n",
+       "      <td>-8.2027</td>\n",
+       "      <td>40.0920</td>\n",
+       "      <td>81.8828</td>\n",
+       "      <td>g</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>31.6036</td>\n",
+       "      <td>11.7235</td>\n",
+       "      <td>2.5185</td>\n",
+       "      <td>0.5303</td>\n",
+       "      <td>0.3773</td>\n",
+       "      <td>26.2722</td>\n",
+       "      <td>23.8238</td>\n",
+       "      <td>-9.9574</td>\n",
+       "      <td>6.3609</td>\n",
+       "      <td>205.2610</td>\n",
+       "      <td>g</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>162.0520</td>\n",
+       "      <td>136.0310</td>\n",
+       "      <td>4.0612</td>\n",
+       "      <td>0.0374</td>\n",
+       "      <td>0.0187</td>\n",
+       "      <td>116.7410</td>\n",
+       "      <td>-64.8580</td>\n",
+       "      <td>-45.2160</td>\n",
+       "      <td>76.9600</td>\n",
+       "      <td>256.7880</td>\n",
+       "      <td>g</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>23.8172</td>\n",
+       "      <td>9.5728</td>\n",
+       "      <td>2.3385</td>\n",
+       "      <td>0.6147</td>\n",
+       "      <td>0.3922</td>\n",
+       "      <td>27.2107</td>\n",
+       "      <td>-6.4633</td>\n",
+       "      <td>-7.1513</td>\n",
+       "      <td>10.4490</td>\n",
+       "      <td>116.7370</td>\n",
+       "      <td>g</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>75.1362</td>\n",
+       "      <td>30.9205</td>\n",
+       "      <td>3.1611</td>\n",
+       "      <td>0.3168</td>\n",
+       "      <td>0.1832</td>\n",
+       "      <td>-5.5277</td>\n",
+       "      <td>28.5525</td>\n",
+       "      <td>21.8393</td>\n",
+       "      <td>4.6480</td>\n",
+       "      <td>356.4620</td>\n",
+       "      <td>g</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    fLength    fWidth   fSize   fConc  fConc1     fAsym  fM3Long  fM3Trans  \\\n",
+       "0   28.7967   16.0021  2.6449  0.3918  0.1982   27.7004  22.0110   -8.2027   \n",
+       "1   31.6036   11.7235  2.5185  0.5303  0.3773   26.2722  23.8238   -9.9574   \n",
+       "2  162.0520  136.0310  4.0612  0.0374  0.0187  116.7410 -64.8580  -45.2160   \n",
+       "3   23.8172    9.5728  2.3385  0.6147  0.3922   27.2107  -6.4633   -7.1513   \n",
+       "4   75.1362   30.9205  3.1611  0.3168  0.1832   -5.5277  28.5525   21.8393   \n",
+       "\n",
+       "    fAlpha     fDist class  \n",
+       "0  40.0920   81.8828     g  \n",
+       "1   6.3609  205.2610     g  \n",
+       "2  76.9600  256.7880     g  \n",
+       "3  10.4490  116.7370     g  \n",
+       "4   4.6480  356.4620     g  "
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cols = [\"fLength\", \"fWidth\", \"fSize\", \"fConc\", \"fConc1\", \"fAsym\", \"fM3Long\", \"fM3Trans\", \"fAlpha\", \"fDist\", \"class\"] # column names\n",
+    "# Reading the csv\n",
+    "df = pd.read_csv(\"magic04.data\", names=cols) # original file has no header, so we provide column names\n",
+    "df.head()\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f904afb3",
+   "metadata": {},
+   "source": [
+    "train test split"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "4fd9c9e7",
+   "metadata": {},
+   "source": [
+    "we split the data into train and test. They can be in any ratio but normally we take 80/20  \n",
+    "X_train has features while y_train has the target result against features so the model can   \n",
+    "know what type of result should be produced for what value"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "f61518fb",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "    fLength    fWidth   fSize   fConc  fConc1     fAsym  fM3Long  fM3Trans  \\\n",
+      "0   28.7967   16.0021  2.6449  0.3918  0.1982   27.7004  22.0110   -8.2027   \n",
+      "1   31.6036   11.7235  2.5185  0.5303  0.3773   26.2722  23.8238   -9.9574   \n",
+      "2  162.0520  136.0310  4.0612  0.0374  0.0187  116.7410 -64.8580  -45.2160   \n",
+      "3   23.8172    9.5728  2.3385  0.6147  0.3922   27.2107  -6.4633   -7.1513   \n",
+      "4   75.1362   30.9205  3.1611  0.3168  0.1832   -5.5277  28.5525   21.8393   \n",
+      "\n",
+      "    fAlpha     fDist  \n",
+      "0  40.0920   81.8828  \n",
+      "1   6.3609  205.2610  \n",
+      "2  76.9600  256.7880  \n",
+      "3  10.4490  116.7370  \n",
+      "4   4.6480  356.4620  \n"
+     ]
+    }
+   ],
+   "source": [
+    "X=df.drop(\"class\", axis=1) # drop the last column which is the target variable meaning we want to predict\n",
+    "y=df[\"class\"] # target variable\n",
+    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)\n",
+    "print(X.head())  # Show the first 5 rows of training features\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ce509197",
+   "metadata": {},
+   "source": [
+    "Standard scalar"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "68c783be",
+   "metadata": {},
+   "source": [
+    "Scale and normalize the data before actually training it.  \n",
+    "This ensures that all featurs contribute equally to model.  \n",
+    "And give a better result after training.  "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "940cafaa",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "scaler = StandardScaler()\n",
+    "X_scaled = scaler.fit_transform(X)\n",
+    "X_train_scaled = scaler.fit_transform(X_train)\n",
+    "X_test_scaled = scaler.transform(X_test)\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "6b69c4ca",
+   "metadata": {},
+   "source": [
+    "Logistic Regresssion  \n",
+    "Used for bianry classification e.g, email classification of spam or not spam"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "e3954e29",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "              precision    recall  f1-score   support\n",
+      "\n",
+      "           g       0.81      0.90      0.85      2460\n",
+      "           h       0.76      0.60      0.67      1344\n",
+      "\n",
+      "    accuracy                           0.79      3804\n",
+      "   macro avg       0.78      0.75      0.76      3804\n",
+      "weighted avg       0.79      0.79      0.79      3804\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Use scaled data for training\n",
+    "model = LogisticRegression(max_iter=1000)\n",
+    "model.fit(X_train_scaled, y_train)\n",
+    "\n",
+    "y_pred = model.predict(X_test_scaled)  # use scaled test data\n",
+    "print(classification_report(y_test, y_pred))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a570f21c",
+   "metadata": {},
+   "source": [
+    "KNN Classifier  \n",
+    "Classication based on nearest neighbours"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "a6fee560",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "              precision    recall  f1-score   support\n",
+      "\n",
+      "           g       0.81      0.90      0.85      2460\n",
+      "           h       0.76      0.60      0.67      1344\n",
+      "\n",
+      "    accuracy                           0.79      3804\n",
+      "   macro avg       0.78      0.75      0.76      3804\n",
+      "weighted avg       0.79      0.79      0.79      3804\n",
+      "\n",
+      "Accuracy: 0.7931125131440588\n"
+     ]
+    }
+   ],
+   "source": [
+    "knn_model = KNeighborsClassifier(n_neighbors=5)\n",
+    "knn_model.fit(X_train_scaled, y_train)\n",
+    "y_pred = model.predict(X_test_scaled)  # use scaled test data\n",
+    "print(classification_report(y_test, y_pred))\n",
+    "print(\"Accuracy:\", accuracy_score(y_test, y_pred))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "bae34d30",
+   "metadata": {},
+   "source": [
+    "Support Vector Classification"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "id": "58453370",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/usr/lib/python3/dist-packages/sklearn/base.py:493: UserWarning: X does not have valid feature names, but SVC was fitted with feature names\n",
+      "  warnings.warn(\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "              precision    recall  f1-score   support\n",
+      "\n",
+      "           g       0.65      0.93      0.77      2460\n",
+      "           h       0.40      0.08      0.14      1344\n",
+      "\n",
+      "    accuracy                           0.63      3804\n",
+      "   macro avg       0.53      0.51      0.45      3804\n",
+      "weighted avg       0.56      0.63      0.55      3804\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "model = SVC(kernel='linear')\n",
+    "model.fit(X_train, y_train)\n",
+    "y_pred = model.predict(X_test_scaled)  # use scaled test data\n",
+    "print(classification_report(y_test, y_pred))"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
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