% The following code applies Simulated Annealing Evolutionary algorithm on a supervised % Model as feature selection. Data is consisted of 300 samples from 6 % Classes (each class 50 samples) alongside with 40 features. The code reduces the features by half % To 20 by selecting best features out of 40. Finally, KNN classification % With proper confusion matrix plot, presents the performance of the % System. You can load your data and define the desired number of features % For it. Also, in order to better performance and depending on your system % Power and your data, play with the SA parameters. % If you find the code hard to understand, please feel free to contact me % Seyed Muhammad Hossein Mousavi % [email protected]