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.

Name		Name	Last commit message	Last commit date
Latest commit History 48 Commits
.gitignore		.gitignore
CFS.py		CFS.py
CFS_ForwardSearch.py		CFS_ForwardSearch.py
FS-CFS.ipynb		FS-CFS.ipynb
FS-D-Tree.ipynb		FS-D-Tree.ipynb
FS-Filters.ipynb		FS-Filters.ipynb
FS-LDA.ipynb		FS-LDA.ipynb
FS-Lasso.ipynb		FS-Lasso.ipynb
FS-PCA.ipynb		FS-PCA.ipynb
FS-Permutation+Wrapper.ipynb		FS-Permutation+Wrapper.ipynb
FS-Permutation-FI.ipynb		FS-Permutation-FI.ipynb
FS-Random-Forest.ipynb		FS-Random-Forest.ipynb
FS-ReliefF.ipynb		FS-ReliefF.ipynb
FS-Wrappers.ipynb		FS-Wrappers.ipynb
HarryPotterTT.csv		HarryPotterTT.csv
README.md		README.md
entropy_estimators.py		entropy_estimators.py
ionosphere.csv		ionosphere.csv
mutual_information.py		mutual_information.py
penguins.csv		penguins.csv
requirements.txt		requirements.txt
segmentation-all.csv		segmentation-all.csv

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