l1l2py is a Python package to perform variable selection by means of l1l2 regularization with double optimization.

A Python package for generating candidate models for multi-model inference

Automated Bidirectional Stepwise Selection On Python

A regularized version of RBM for unsupervised feature selection.

Stepwise regression fits a logistic regression model in which the choice of predictive variables is carried out by an automatic forward stepwise procedure.

Code and simulations using an Ensemble of Single-Effect Neural Networks (ESNN)

Source Code for Paper "Bayesian MI-LASSO for variable selection on multiply-imputed data" (Arxiv: https://arxiv.org/abs/2211.00114)

Topological data analytic approach for discovering biophysical signatures in protein dynamics

sliced: scikit-learn compatible sufficient dimension reduction

Estimating Copula Entropy (Mutual Information), Transfer Entropy (Conditional Mutual Information), and the statistics for multivariate normality test and two-sample test, and change point detection in Python