项目作者: JingweiToo

项目描述 :
Application of Henry Gas Solubility Optimization (HGSO) in the feature selection tasks.
高级语言: MATLAB
项目地址: git://github.com/JingweiToo/Henry-Gas-Solubility-Optimization-for-Feature-Selection.git
创建时间: 2021-01-04T03:23:58Z
项目社区:https://github.com/JingweiToo/Henry-Gas-Solubility-Optimization-for-Feature-Selection

开源协议:BSD 3-Clause "New" or "Revised" License

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Henry Gas Solubility Optimization for Feature Selection

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License
GitHub release

Wheel

Introduction

  • This toolbox offers a Henry Gas Solubility Optimization ( HGSO ) method
  • The Main file illustrates the example of how HGSO can solve the feature selection problem using benchmark data-set.

Input

  • feat : feature vector ( Instances x Features )
  • label : label vector ( Instances x 1 )
  • N : number of gas
  • max_Iter : maximum number of iterations
  • num_clus : Number of gas types
  • K : Constant
  • alpha : Influence of other gas
  • beta : Constant
  • L1 : Initial parameter
  • L2 : Initial parameter
  • L3 : Initial parameter

Output

  • sFeat : selected features
  • Sf : selected feature index
  • Nf : number of selected features
  • curve : convergence curve

Example

  1. % Benchmark data set
  2. load ionosphere.mat;
  3. % Set 20% data as validation set
  4. ho = 0.2;
  5. % Hold-out method
  6. HO = cvpartition(label,'HoldOut',ho);
  7. % Parameter setting
  8. N = 10;
  9. max_Iter = 100;
  10. num_clus = 2; % number of gas types / cluster
  11. K = 1; % constant
  12. alpha = 1; % influence of other gas
  13. beta = 1; % constant
  14. L1 = 5E-3;
  15. L2 = 100;
  16. L3 = 1E-2;
  17. % Henry Gas Solubility Optimization
  18. [sFeat,Sf,Nf,curve] = jHGSO(feat,label,N,max_Iter,num_clus,K,alpha,beta,L1,L2,L3,HO);
  19. % Plot convergence curve
  20. plot(1:max_Iter,curve);
  21. xlabel('Number of iterations');
  22. ylabel('Fitness Value');
  23. title('HGSO'); grid on;

Requirement

  • MATLAB 2014 or above
  • Statistics and Machine Learning Toolbox