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

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• Updated Oct 2, 2024
• Python

Case studies on model assessment, model selection and inference after model selection

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• Updated Jan 9, 2024
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Developer Version of the R package CAST: Caret Applications for Spatio-Temporal models

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• Updated Sep 24, 2026
• R

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• Updated Nov 26, 2018
• Jupyter Notebook

Projection predictive variable selection

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• Updated Nov 12, 2026
• R

Boosting algorithms for fitting generalized linear, additive and interaction models to potentially high-dimensional data. The current relase version can be found on CRAN (http://cran.r-project.org/package=mboost).

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• Updated Sep 22, 2026
• HTML

Bayesian additive regression trees (BART) for regression, classification, uncertainty quantification, and variable selection in R, with optional GPU acceleration.

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• Updated Sep 3, 2026
• HTML

BAS R package for Bayesian Model Averaging and Variable Selection

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• Updated May 7, 2026
• C

Python library for selecting diverse data subsets for machine-learning. Webserver: https://huggingface.co/spaces/QCDevs/Selector.

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• Updated Oct 20, 2026
• Jupyter Notebook

R package for estimating copula entropy (mutual information), transfer entropy (conditional mutual information), and the statistic for multivariate normality test and two-sample test

r correlation entropy information-theory variable-selection causality copula mutual-information transfer-entropy conditional-mutual-information granger-causality change-point-detection causal-discovery two-sample-test mutualinf copula-entropy normality-test conditional-independence-test

• Updated Jun 7, 2024
• R

Feature Selection and Variable Selection: papers and methods

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• Updated Oct 24, 2026

OmicSelector - Environment, docker-based application and R package for biomarker signiture selection (feature selection) & deep learning diagnostic tool development from high-throughput high-throughput omics experiments and other multidimensional datasets. Initially developed for miRNA-seq, RNA-seq and qPCR.

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• Updated Oct 30, 2026
• R

Data preparation for data science projects.

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• Updated Sep 2, 2025
• R

Performs Variables selection and model tuning for Species Distribution Models (SDMs). It provides also several utilities to display results.

variable-selection species-distribution-modelling hyperparameter-tuning

• Updated Aug 27, 2025
• R

Boosting models for fitting generalized additive models for location, shape and scale (GAMLSS) to potentially high dimensional data. The current relase version can be found on CRAN (https://cran.r-project.org/package=gamboostLSS).

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• Updated Sep 17, 2026
• R

Stability Selection with Error Control

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• Updated Jan 30, 2026
• R

Penalized least squares estimation using the Orthogonalizing EM (OEM) algorithm

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• Updated Nov 10, 2026
• C++

python voting variable-selection feature-selection

• Updated Dec 13, 2019
• Jupyter Notebook

Code and simulations using biologically annotated neural networks

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• Updated Aug 23, 2021
• HTML

Boosting Functional Regression Models. The current release version can be found on CRAN (http://cran.r-project.org/package=FDboost).

machine-learning cran variable-selection boosting-algorithms boosting function-on-function-regression scalar-on-function-regression function-on-scalar-regression

• Updated Apr 12, 2026
• R