cefeste 1.1.0

Feature Selection and Elimination

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:

1. 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 )
2. Install the package:
   • User Mode: pip install ce-feste

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