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scikit-learn, Feature Selection sklearn.feature_selection, Correct…

- - - - GenericUnivariateSelect
        selects features based on the mode (percentile / kbest/fpr/fwe/fdr) and appropriate parameters
      - SelectFpr
        based on a false positive rate test
      - SelectFdr
        based on an estimated false discovery rate
      - SelectFwe
        based on family-wise error rate
      - SelectKBest
        selects k highest scoring features
        based on given univariate scoring function
      - SelectPercentile
        Selects user-specified highest scoring % of features
        based on given univariate scoring function
  - - - mutual_info_regression
      - mutual_info_classif
    - - chi2
        (classification only)
    - - f_regression
      - f_classif
- - - - make_regression
      - make_blobs
      - make_classification
      - make_multi_classification
- - - - Transform
        
        Select Features
- - - - .predict()
      - .score