variable-selection

There are 4 repositories under variable-selection topic.

avehtari / modelselection
Case studies on model assessment, model selection and inference after model selection
bayesian variable-selection stan rstanarm
Language:HTML 170
Sundar0989 / WOE-and-IV
weight-of-evidence information-value variable-selection woe iv woe-and-iv
Language:Jupyter Notebook 136
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
copula-entropy mutual-information causal-discovery variable-selection granger-causality transfer-entropy correlation normality-test information-theory causality python copula hypothesis-testing two-sample-test conditional-independence-test conditional-mutual-information change-point-detection entropy change-detection changepoint
Language:Python 132
stan-dev / projpred
Projection predictive variable selection
rstanarm statistics bayesian variable-selection stan bayesian-inference r-package
Language:R 108
HannaMeyer / CAST
Developer Version of the R package CAST: Caret Applications for Spatio-Temporal models
caret machine-learning autocorrelation spatial spatio-temporal overfitting feature-selection variable-selection predictive-modeling
Language:R 100
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).
mboost cran boosting-algorithms tutorials machine-learning r-language variable-selection modelling gam glm r-package
Language:HTML 71
merliseclyde / BAS
BAS R package https://merliseclyde.github.io/BAS/
bayesian predictive-modeling model-selection mcmc r-package cran regression variable-selection bayesian-inference
Language:C 41
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
copula entropy estiamtion mutualinf copula-entropy causal-discovery variable-selection transfer-entropy granger-causality correlation normality-test information-theory mutual-information r machine-learning causality two-sample-test conditional-independence-test conditional-mutual-information
Language:R 38
ELToulemonde / dataPreparation
Data preparation for data science projects.
data-preparation data-science date-conversion variable-selection variable-elimination r data-preprocessing speed
Language:R 31
mlpapers / feature-selection
Awesome papers on Feature Selection
feature-selection feature-importance variable-selection mutual-information correlation dimensionality-reduction awesome awesome-list
31
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.
feature-selection omics r r-package classification data-science data-mining bioinformatics bioinformatics-pipeline biomarkers biomarker-discovery docker-image variable-selection deep-learning deep-neural-networks next-generation-sequencing neural-network rna-seq qpcr mirna
Language:R 30
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).
gamboostlss cran gamlss r-package variable-selection machine-learning boosting-algorithms r-language
Language:R 26
Sundar0989 / Variable-Selection-Using-Python
variable-selection python feature-selection voting
Language:Jupyter Notebook 26
hofnerb / stabs
Stability Selection with Error Control
stability-selection cran r-package r-language variable-selection variable-importance machine-learning resampling
Language:R 25
jaredhuling / oem
Penalized least squares estimation using the Orthogonalizing EM (OEM) algorithm
variable-selection cran r-package machine-learning penalized-regression lasso group-lasso oem oem-algorithm mcp scad
Language:C++ 25
ConsBiol-unibern / SDMtune
Performs Variables selection and model tuning for Species Distribution Models (SDMs). It provides also several utilities to display results.
hyperparameter-tuning species-distribution-modelling variable-selection
Language:R 23
theochem / Selector
Methods for selecting diverse (molecular) database.
chemical-diversity compound-selection maximum-diversity-molecule maximum-dissimilarity-search variable-selection compound-acquisition chemical-library-design
Language:Jupyter Notebook 21
BANNs
lcrawlab / BANNs
Code and simulations using biologically annotated neural networks
gwas neural-networks machine-learning interpretability genetics variable-selection bayesian-statistics gwas-tools
Language:HTML 20
joshloyal / sliced
sliced: scikit-learn compatible sufficient dimension reduction
dimension-reduction dimensionality-reduction feature-selection machine-learning machine-learning-algorithms python sufficient-dimension-reduction variable-selection
Language:Python 19
lorinanthony / RATE
Code for Variable Selection in Black Box Methods with RelATive cEntrality (RATE) Measures
gp-regression variable-selection variable-importance neural-networks bayesian-neural-networks kullback-leibler-divergence genetics deep-neural-networks machine-learning
Language:Jupyter Notebook 19
majianthu / aps2020
Code for the paper 'Variable Selection with Copula Entropy' published on Chinese Journal of Applied Probability and Statistics
variable-selection feature-selection variable-importance feature-engineering copula-entropy mutual-information distance-correlation hsic
Language:R 17
Mamba413 / bess
Best Subset Selection algorithm for Regression, Classification, Count, Survival analysis
variable-selection feature-selection regression-models classification-model survival-analysis poisson-regression sparse-linear-systems
Language:C++ 17
boost-R / FDboost
Boosting Functional Regression Models. The current release version can be found on CRAN (http://cran.r-project.org/package=FDboost).
cran boosting-algorithms boosting function-on-function-regression scalar-on-function-regression function-on-scalar-regression machine-learning variable-selection
Language:R 16
meowoodie / Regularized-RBM
A regularized version of RBM for unsupervised feature selection.
data-mining embeddings events feature-selection icassp icassp-2018 l1 machine-learning python rbm regularization skipgram statistics tensorflow unsupervised-learning variable-selection
Language:Python 13
nanxstats / msaenet
🧲 Multi-step adaptive estimation for reducing false positive selection in sparse regressions
false-positive-control high-dimensional-data linear-regression machine-learning variable-selection
Language:R 13
lorinanthony / BAKR
Code and Simulations using Bayesian Approximate Kernel Regression (BAKR)
nonlinear-regression variable-selection gwas genetics bayesian-statistics kernel-regression
Language:C++ 11
hruffieux / locus
locus R package - Large-scale variational inference for variable selection in sparse multiple-response regression
variable-selection joint-models high-dimensional-data sparse-regression variational-inference biostatistics
Language:R 10
slipguru / l1l2py
l1l2py is a Python package to perform variable selection by means of l1l2 regularization with double optimization.
python machinelearning variable-selection feature-selection fista l1l2-regularization
Language:Python 9
emirhankartal-py / python_bidirectional_stepwise_selection
Automated Bidirectional Stepwise Selection On Python
feature-selection feature python stepwise-regression bidirectional features variable-selection variable-importance forward backward machine-learning data science
Language:Python 8
SINATRA
lcrawlab / SINATRA
A statistical framework for feature selection and association mapping with 3D shapes
topological-data-analysis shape-analysis shape-reconstruction nonparametric-regression variable-selection 3d-reconstruction 3d-shapes euler-characteristics topological-summary-statistics topological-features centrality-measures r-package r
Language:R 8
biona001 / Knockoffs.jl
Variable Selection with Knockoffs
bioinformatics conditional-independence conditional-independence-test false-discovery-rate fdr feature-selection genomics group-knockoffs hypothesis-testing knockoff-filter knockoffs lasso model-selection multiple-knockoffs variable-selection
Language:Julia 7
abhianik / dpdSIS
Robust Sure Independence Screening using the Minimum Density Power Divergence Estimators
high-dimensional-data variable-selection robust-statistics
Language:R 6
Mamba413 / cdcsis
Conditional Distance Correlation based Statistical Method
conditional-dependence variable-selection feature-selection
Language:C++ 6
nanxstats / OHPL
📈 Ordered Homogeneity Pursuit Lasso for Group Variable Selection
variable-selection partial-least-squares-regression spectroscopy lasso high-dimensional-data homogeneity-pursuit chemometrics
Language:R 6
agugonrey / MOSS
MOSS: Multi-Omic integration via Sparse Singular Decomposition
multi-omic-integration sparse-singular-value-decomposition variable-selection elastic-net r-package
Language:R 5
htpusa / scanoncorr
Sparse canonical correlation analysis
canonical-correlation-analysis matlab multivariate-analysis variable-selection sparse-canonical-correlation
Language:MATLAB 5