Python package for regularized regressions.
Supported regularization terms:
- Ridge
- LASSO
- Network-fusion penalty (https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6030897/)
$ pip install reggy
A simple example with LASSO regularization:
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]]