Update README.md

Author: JingweiToo

README.md

@@ -1 +1,58 @@
-# Whale-Optimization-Algorithm-for-Feature-Selection
+# Whale Optimization Algorithm for Feature Selection
+
+[![License](https://img.shields.io/badge/license-BSD_3-yellow.svg)](https://github.com/JingweiToo/Whale-Optimization-Algorithm-for-Feature-Selection/blob/main/LICENSE)
+[![GitHub release](https://img.shields.io/badge/release-1.1-green.svg)](https://github.com/JingweiToo/Whale-Optimization-Algorithm-for-Feature-Selection)
+
+![Wheel](https://www.mathworks.com/matlabcentral/mlc-downloads/downloads/935b0716-70d6-40b6-a4ad-3b479f499e2e/f587998c-2aef-4bd2-ba65-b056e2d10146/images/1603176127.JPG)
+
+
+## Introduction
+* This toolbox offers a Whale Optimization Algorithm ( WOA ) method
+* The `Main` script illustrates the example of how WOA can solve the feature selection problem using benchmark dataset
+
+
+## Input
+* *`feat`*     : feature vector ( Instances *x* Features )
+* *`label`*    : label vector ( Instances *x* 1 )
+* *`N`*        : number of whales
+
+
+## Output
+* *`sFeat`*    : selected features
+* *`Sf`*       : selected feature index
+* *`Nf`*       : number of selected features
+* *`curve`*    : convergence curve
+
+
+### Example
+```code
+% Benchmark data set 
+load ionosphere.mat;
+
+% Set 20% data as validation set
+ho=0.2; 
+% Hold-out method
+HO=cvpartition(label,'HoldOut',ho);
+
+% Parameter setting
+N        = 10; 
+max_Iter = 100; 
+
+% Whale Optimization Algorithm
+[sFeat,Sf,Nf,curve] = jWOA(feat,label,N,max_Iter,HO);
+
+% Accuracy
+Acc = jKNN(sFeat,label,HO); 
+fprintf('\n Accuracy: %g %%',Acc); fprintf('\n');
+
+% Plot convergence curve
+plot(1:max_Iter,curve); 
+xlabel('Number of Iterations');
+ylabel('Fitness Value');
+title('WOA'); grid on;
+```
+
+## Requirement
+* MATLAB 2014 or above
+* Statistics and Machine Learning Toolbox
+