variable-selection

There are 149 repositories under variable-selection topic.

  • avehtari/modelselection

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

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  • majianthu/pycopent

    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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  • Sundar0989/WOE-and-IV

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  • HannaMeyer/CAST

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

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  • stan-dev/projpred

    Projection predictive variable selection

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  • boost-R/mboost

    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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  • merliseclyde/BAS

    BAS R package for Bayesian Model Averaging and Variable Selection

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  • majianthu/copent

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

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  • OmicSelector

    kstawiski/OmicSelector

    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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  • mlpapers/feature-selection

    Awesome papers on Feature Selection

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  • ELToulemonde/dataPreparation

    Data preparation for data science projects.

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  • jaredhuling/oem

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

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  • boost-R/gamboostLSS

    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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  • hofnerb/stabs

    Stability Selection with Error Control

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  • Sundar0989/Variable-Selection-Using-Python

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  • ConsBiol-unibern/SDMtune

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

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  • joshloyal/sliced

    sliced: scikit-learn compatible sufficient dimension reduction

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  • theochem/Selector

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

    Language:Jupyter Notebook2296522
  • BANNs

    lcrawlab/BANNs

    Code and simulations using biologically annotated neural networks

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  • boost-R/FDboost

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

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  • lorinanthony/RATE

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

    Language:Jupyter Notebook19204

  • majianthu/aps2020

    Code for the paper 'Variable Selection with Copula Entropy' published on Chinese Journal of Applied Probability and Statistics

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  • Mamba413/bess

    Best Subset Selection algorithm for Regression, Classification, Count, Survival analysis

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  • meowoodie/Regularized-RBM

    A regularized version of RBM for unsupervised feature selection.

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  • nanxstats/msaenet

    šŸ§² Multi-step adaptive estimation for reducing false positive selection in sparse regressions

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  • ducnh279/Variable-Selection-Network-with-PyTorch

    Variable Selection Network with PyTorch

    Language:Jupyter Notebook11104

  • lorinanthony/BAKR

    Code and Simulations using Bayesian Approximate Kernel Regression (BAKR)

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  • hruffieux/locus

    locus R package - Large-scale variational inference for variable selection in sparse multiple-response regression

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  • emirhankartal-py/python_bidirectional_stepwise_selection

    Automated Bidirectional Stepwise Selection On Python

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  • slipguru/l1l2py

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

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  • biona001/GhostKnockoffGWAS

    Knockoff-based analysis of GWAS summary statistics data

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  • SINATRA

    lcrawlab/SINATRA

    A statistical framework for feature selection and association mapping with 3D shapes

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  • biona001/Knockoffs.jl

    Variable Selection with Knockoffs

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  • htpusa/scanoncorr

    Sparse canonical correlation analysis

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  • JacobSeedorff21/BranchGLM

    Efficient Variable Selection for GLMs in R

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  • TuoooLiu666/Applied-Biostatistics-Projects

    This repository commits to the application of biostatistics knowledge on clinical, randomized trials and observational studies.

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