Model-Selection Classification
In machine learning, Classification is a subcategory of supervised learning. Classification is the problem of identifying to which of a set of categories, a new observation belongs, on the basis of a training set of data containing observations whose category membership is known. Classification is one of the most widely used techniques in machine learning, for medical diagnosis and image classification etc. Linear classifiers are among the most practical classification methods. In this project, we have provided with 4 different Train datasets (Psoriasis, Lupus, Autism, Psoriasis RNAseq) and one dataset for each case in order to predict the labels of their samples. All data downloaded from https://inclass.kaggle.com/.