Feature selection caused more overfitting2019 Community Moderator ElectionHow does SelectKBest() perform feature selection?Sklearn feature selection stopping criterion (SelectFromModel)Feature selection where adding features are deteriorating modelFeature reduction convenienceIntuitive interpretation of ratios between training set scores and validation set scoreswhy the RFE to select features is changing when the os or computer is changedOverfitting problem in modelFeature Scaling and normalization in cross-validation setReasons why training error can go up after more training?Manual feature engineering based on the output

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Feature selection caused more overfitting



2019 Community Moderator ElectionHow does SelectKBest() perform feature selection?Sklearn feature selection stopping criterion (SelectFromModel)Feature selection where adding features are deteriorating modelFeature reduction convenienceIntuitive interpretation of ratios between training set scores and validation set scoreswhy the RFE to select features is changing when the os or computer is changedOverfitting problem in modelFeature Scaling and normalization in cross-validation setReasons why training error can go up after more training?Manual feature engineering based on the output










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What does it mean if I used selectfrommodel to select features and cross-validation score went up but the test set score went down even more compared to when I did not use feature selection?
Does this mean it's causing more overfitting? I thought feature selection is used to reduce overfitting.










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    $begingroup$


    What does it mean if I used selectfrommodel to select features and cross-validation score went up but the test set score went down even more compared to when I did not use feature selection?
    Does this mean it's causing more overfitting? I thought feature selection is used to reduce overfitting.










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      $begingroup$


      What does it mean if I used selectfrommodel to select features and cross-validation score went up but the test set score went down even more compared to when I did not use feature selection?
      Does this mean it's causing more overfitting? I thought feature selection is used to reduce overfitting.










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      What does it mean if I used selectfrommodel to select features and cross-validation score went up but the test set score went down even more compared to when I did not use feature selection?
      Does this mean it's causing more overfitting? I thought feature selection is used to reduce overfitting.







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