├── .github └── workflows │ └── python-package.yml ├── .gitignore ├── 1_Demo_Data_Explore.ipynb ├── 2.1_Demo_Missing_Data.ipynb ├── 2.2_Demo_Outlier.ipynb ├── 2.3_Demo_Rare_Values.ipynb ├── 3.1_Demo_Feature_Scaling.ipynb ├── 3.2_Demo_Discretisation.ipynb ├── 3.3_Demo_Feature_Encoding.ipynb ├── 3.4_Demo_Feature_Transformation.ipynb ├── 3.5_Demo_Feature_Generation.ipynb ├── 4.1_Demo_Feature_Selection_Filter.ipynb ├── 4.2_Demo_Feature_Selection_Wrapper.ipynb ├── 4.3_Demo_Feature_Selection_Embedded.ipynb ├── 4.4_Demo_Feature_Selection_Feature_Shuffling.ipynb ├── 4.5_Demo_Feature_Selection_Hybrid_method.ipynb ├── A Short Guide for Feature Engineering and Feature Selection.md ├── A Short Guide for Feature Engineering and Feature Selection.pdf ├── README.md ├── data ├── housing.data.txt ├── pima-indians-diabetes.data.csv └── titanic.csv ├── data_exploration └── explore.py ├── feature_cleaning ├── missing_data.py ├── outlier.py └── rare_values.py ├── feature_engineering ├── discretization.py ├── encoding.py └── transformation.py ├── feature_selection ├── embedded_method.py ├── feature_shuffle.py ├── filter_method.py └── hybrid.py ├── images ├── 001.png ├── IV.png ├── box-cox.png ├── embedded.png ├── featuretools.png ├── filter.png ├── scaling.png ├── sphx_glr_plot_map_data_to_normal_001.png ├── workflow2.png └── wrapper.png └── output ├── Barplot_Pclass_Survived.png ├── Boxplot_Pclass_Fare.png ├── Corr_plot.png ├── Countplot_Pclass.png ├── Distplot_Fare.png ├── Heatmap.png ├── Scatter_plot_Fare_Pclass.png ├── describe.csv └── missing.csv /.github/workflows/python-package.yml: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/ashishpatel26/Amazing-Feature-Engineering/HEAD/.github/workflows/python-package.yml -------------------------------------------------------------------------------- /.gitignore: -------------------------------------------------------------------------------- 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