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14 search results found

Pycopent ⭐ 101

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

Developer Version of the R package CAST: Caret Applications for Spatio-Temporal models

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).

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

Gamboostlss ⭐ 24

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).

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

Stability Selection with Error Control

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

🧲 Multi-step adaptive estimation for reducing false positive selection in sparse regressions

Code for Variable Selection in Black Box Methods with RelATive cEntrality (RATE) Measures

Code and simulations using Biologically Annotated Neural Networks (BANNs)

Regularized Rbm ⭐ 7

A regularized version of RBM for unsupervised feature selection.

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

Bcpm Msaenet ⭐ 5

Solution for the precisionFDA Brain Cancer Predictive Modeling Challenge using msaenet

Vennlasso ⭐ 5

Variable selection for heterogeneous populations using the vennLasso penalty

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