文件名称:FeatureSelection_MachineLearning
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Feature selection methods for machine learning algorithms such as SVR, including one filter-based method (CFS) and two wrapper-based methods (GA and PSO). The gridsearch is for the grid search for the optimal hyperparemeters of SVR. The SVM_CV is for the k-fold cross-validation of SVR. All the programs are flexible and could be implemented by the users themselves.-Feature selection methods for machine learning algorithms such as SVR, including one filter-based method (CFS) and two wrapper-based methods (GA and PSO). The gridsearch is for the grid search for the optimal hyperparemeters of SVR. The SVM_CV is for the k-fold cross-validation of SVR. All the programs are flexible and could be implemented by the users themselves.
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下载文件列表
FeatureSelection_MachineLearning/CFS.m
FeatureSelection_MachineLearning/GAFS.m
FeatureSelection_MachineLearning/gridSearch.m
FeatureSelection_MachineLearning/PSOFS.m
FeatureSelection_MachineLearning/SVR_CV.m
FeatureSelection_MachineLearning/
FeatureSelection_MachineLearning/GAFS.m
FeatureSelection_MachineLearning/gridSearch.m
FeatureSelection_MachineLearning/PSOFS.m
FeatureSelection_MachineLearning/SVR_CV.m
FeatureSelection_MachineLearning/
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