Feature Selection and Elimination
Project description
Credito Emiliano - Fe**ature Selection, Transformation and Elimination (CE - FeSTE)
This repo contains the 'FeSTE' python package which helps in the features management from the pre-filtering to the pre-processing and feature elimination.
Installation
To install it:
- Optional: create a new Python virtual environment (through bash terminal run: "py -m venv your_env_name" and then "source your_env_name/Scripts/activate )
- Install the package:
- User Mode:
pip install ce-feste
- User Mode:
Structure
The .py package is stored in src and contains 3 sub-modules:
- selection: contains the feature preliminary selection functions
- transform: contains the feature pre-processing functions
- elimination: contains the feature elimination functions
Filters
Selection
- Univariate filters:
- No constant features
- Number of distinct value too low
- Number of missing values too high
- Too concentrate in the most frequent value
- Unstable between sets
- Multivariate filters:
- Spearman Correlation for numerical features
- Cramer's V for categorical features
- R2 for mixed features
- VIF
- Explanatory filters:
- Feature AUROC for classification
- Feature Correlation with target for regression
Elimination
- Shap Recursive Feature Elimination with HyperParam Optimization
Trasformation
- Only 2 classes added to select and rename columns in datasets. Useful for generating the production pipeline
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