ksfeatureselector 0.1.0

Select features using Kolmogorov–Smirnov (K-S) test for binary classification tasks.

KSFeatureSelector

KSFeatureSelector is a lightweight Python package for selecting the most discriminatory features in a binary classification problem using the Kolmogorov–Smirnov (K-S) test.

Features

• Uses the K-S test to rank features by their ability to separate classes.
• Supports filtering features by:
  • A maximum p-value threshold.
  • A fixed number of top features.
• Easy-to-read, numpy-style docstrings and validations.
• Pure Python + pandas + scipy.

Installation

• bash pip install ksfeatureselector

• local pip install .

Usage

from ksfeatureselector import select_ks_features

# Your DataFrame `df` should contain numerical features and a binary target column
x_cols = ['feature1', 'feature2', 'feature3']
y_var = 'target'

# Select top features based on p-value or top-n count
select_ks_features(df, x_cols, y_var, top_p=0.05)
# or
select_ks_features(df, x_cols, y_var, top_n=5)

License

- MIT License

Author

-- V Subrahmanya Raghu Ram Kishore Parupudi
-- email: [e-mail]