Simulated-Annealing-SA-Metaheuristic-Feature-Selection

Simulated-Annealing-SA-Metaheuristic-Feature-Selection
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Updated 28 Dec 2021

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% 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 % mosavi.a.i.buali@gmail.com

Cite As

S. Muhammad Hossein Mousavi (2024). Simulated-Annealing-SA-Metaheuristic-Feature-Selection (https://www.mathworks.com/matlabcentral/fileexchange/104245-simulated-annealing-sa-metaheuristic-feature-selection), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2019a
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Version Published Release Notes
1.0.0