https://github.com/kpj/reggy

Python package for regularized regressions.
https://github.com/kpj/reggy

Last synced: 24 days ago
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Python package for regularized regressions.

• Host: GitHub
• URL: https://github.com/kpj/reggy
• Owner: kpj
• License: mit
• Created: 2022-01-20T00:10:27.000Z (over 3 years ago)
• Default Branch: master
• Last Pushed: 2022-09-12T19:55:44.000Z (over 2 years ago)
• Last Synced: 2025-02-18T09:37:41.214Z (3 months ago)
• Language: Python
• Homepage:
• Size: 26.4 KB
• Stars: 3
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# reggy

[![PyPI](https://img.shields.io/pypi/v/reggy.svg?style=flat)](https://pypi.python.org/pypi/reggy)

[![Tests](https://github.com/kpj/reggy/workflows/Tests/badge.svg)](https://github.com/kpj/reggy/actions)

Python package for regularized regressions.

Supported regularization terms:

* Ridge

* LASSO

* Network-fusion penalty (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6030897/)

## Installation

```bash

$ pip install reggy

```

## Usage

A simple example with LASSO regularization:

```python

import reggy

import numpy as np

alpha = 0.3

beta = 1.7

X = np.random.normal(size=(100, 1))

y = np.random.normal(X * beta + alpha, size=(100, 1))

model = reggy.RegReg(X, y, family=reggy.gaussian_family, regularizers=[(0.5, reggy.lasso)])

model.fit()

print(model.intercept_, model.coef_)

## [[0.22491232]] [[0.9219889]]

```