Backwards Regression Python Library - Automated feature selection in linear and logistic regression models.
Project description
Backwards Regression Python Library - Automated feature selection in linear and logistic regression models.
The Backwards Regression Python Library is an open-source toolkit for automated feature selection in regression models. It supports both linear and logistic regression, dynamically selecting the appropriate method based on the target variable.
Installation
pip install backwards_regression
Load Package
## Load Package
from backwards_regression import fit_logistic
from backwards_regression import fit_linear
Usage
## (Linear) With interactions included - set to True and Without Interactions included - set to False
result, dropped_vars = fit_linear(X, y, threshold_in=0.01, threshold_out=0.05, include_interactions=True, verbose=True)
## Print Selected features
print("Final included features:", result)
## Print Eliminated features
print("Dropped variables:", dropped_vars)
## (Logistic) With interactions included - set to True and Without Interactions included - set to False
result, dropped_vars = fit_logistic(X, y, threshold_in=0.01, threshold_out=0.05, include_interactions=True, verbose=True)
## Print Selected features
print("Final included features:", result)
## Print Eliminated features
print("Dropped variables:", dropped_vars)
Key Features
- Automated backward regression for linear and logistic regression models.
- Inclusion and exclusion of features based on user-defined significance thresholds.
- Optional inclusion of interaction terms for enhanced model complexity.
This library is suitable for data scientists, researchers, and practitioners working with regression problems who seek a streamlined approach to feature selection. The library intelligently adapts to the nature of the target variable, supporting both linear and logistic regression models.
Documentation & Examples
For documentation and usage examples, visit the GitHub repository: https://github.com/knowusuboaky/backwardsreg
Author: Kwadwo Daddy Nyame Owusu - Boakye
Email: kwadwo.owusuboakye@outlook.com
License: MIT
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Hashes for backwards_regression-0.1.0.tar.gz
Algorithm | Hash digest | |
---|---|---|
SHA256 | fc5676eb59959e29aa09592f432c2fb8ee7b2022f3f50d30bc9d40547a9f8967 |
|
MD5 | aeb22356ecfef7297b9631b437c4cff0 |
|
BLAKE2b-256 | 71aeda09693538df2d84d27b80729f81855ee8f73b08bdef59ac5ce82e4972ee |