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FeatSelTutorial

Python notebooks for the tutorial paper on feature selection

  • FS-Wrappers: Code for SFS and BE Wrappers from mlxtend.
  • FS-Filters: Code for using I-Gain and Chi-square Filters from scikit-learn.
  • FS-Permutation-FI: Code for using Permutation Feature Importance Filters from scikit-learn.
  • FS-D-Tree: Building D-Trees with embedded feature selction using scikit-learn.
  • FS-Lasso: Feature selection for Logistic Regression using scikit-learn.
  • FS-Permutation+Wrapper: A two stage strategy using Permutation FI and Wrapper.
  • FS-ReliefF: Code for using ReliefF Filters from skrebate.
  • FS-Random-Forest: Feature importance from Random Forest using scikit-learn.
  • FS-CFS: Correlation Based feature importance using code from from https://github.com/jundongl/scikit-feature.
  • FS-PCA: Principal Component Analysis using the PCA implementation in scikit-learn.
  • FS-LDA: Linear Discriminant Analysis using the LDA implementation in scikit-learn.

Data Files