% 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]
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Simulated Annealing (SA) Metaheuristic Feature Selection
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