R machine learning libraries

MXNetapache/incubator-mxnet Archived

Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Go, JavaScript and more.

CatBoostcatboost/catboost

General purpose gradient boosting on decision trees library with categorical features support out of the box. It is easy to install, contains fast inference implementation and supports CPU and GPU (even multi-GPU) computation.

H2Oh2oai/h2o-3

ML engine that supports distributed learning on Hadoop, Spark or your laptop via APIs in R, Python, Scala, REST/JSON.

ggplot2tidyverse/ggplot2

A data visualization package based on the grammar of graphics.

shinyrstudio/shiny

Is the basis for truly interactive displays and dashboards in R. However, some measure of interactivity can be achieved with htmlwidgets bringing javascript libraries to R. These include, plotly, dygraphs, highcharter, and several others.

dplyrtidyverse/dplyr

A data manipulation package that helps to solve the most common data manipulation problems.

data.tableRdatatable/data.table

Data.table provides a high-performance version of base R’s data.frame with syntax and feature enhancements for ease of use, convenience and programming speed.

Machine Learning For Hackersjohnmyleswhite/ML_for_Hackers

Code accompanying the book "Machine Learning for Hackers"

mlrmlr-org/mlr

Mlr: Machine Learning in R.

carettopepo/caret

Classification and Regression Training: Unified interface to ~150 ML algorithms in R.

forecastrobjhyndman/forecast

Forecast: Timeseries forecasting using ARIMA, ETS, STLM, TBATS, and neural network models.

tmapr-tmap/tmap

For visualizing geospatial data with static maps and leaflet for interactive maps

igraphigraph/rigraph

Binding to igraph library - General purpose graph library.

XGBoost.Rtqchen/xgboost

R binding for eXtreme Gradient Boosting (Tree) Library.

Optunityclaesenm/optunity

A library dedicated to automated hyperparameter optimization with a simple, lightweight API to facilitate drop-in replacement of grid search. Optunity is written in Python but interfaces seamlessly with MATLAB.

TDSP-UtilitiesAzure/Azure-TDSP-Utilities Archived

Two data science utilities in R from Microsoft: 1) Interactive Data Exploration, Analysis, and Reporting (IDEAR); 2) Automated Modelling and Reporting (AMR).

SuperLearnerecpolley/SuperLearner

Multi-algorithm ensemble learning packages.

randomForestSRCkogalur/randomForestSRC

RandomForestSRC: Random Forests for Survival, Regression and Classification (RF-SRC).

L0Learnhazimehh/L0Learn

L0Learn: Fast algorithms for best subset selection.

clugenrclugen/clugenr

Multidimensional cluster generation in R.

ahazcran.r-project.org Deprecated

Ahaz: Regularization for semiparametric additive hazards regression.

arulescran.r-project.org

Arules: Mining Association Rules and Frequent Itemsets

biglassocran.r-project.org

Biglasso: Extending Lasso Model Fitting to Big Data in R.

bmrmcran.r-project.org

Bmrm: Bundle Methods for Regularized Risk Minimization Package.

Borutacran.r-project.org

Boruta: A wrapper algorithm for all-relevant feature selection.

bstcran.r-project.org

Bst: Gradient Boosting.

C50cran.r-project.org

C50: C5.0 Decision Trees and Rule-Based Models.

caretEnsemblecran.r-project.org Deprecated

CaretEnsemble: Framework for fitting multiple caret models as well as creating ensembles of such models.

Clever Algorithms For Machine Learningmachinelearningmastery.com

CORElearncran.r-project.org Deprecated

CORElearn: Classification, regression, feature evaluation and ordinal evaluation. -* CoxBoost - CoxBoost: Cox models by likelihood based boosting for a single survival endpoint or competing risks

Cubistcran.r-project.org

Cubist: Rule- and Instance-Based Regression Modelling.

e1071cran.r-project.org

E1071: Misc Functions of the Department of Statistics (e1071), TU Wien

earthcran.r-project.org

Earth: Multivariate Adaptive Regression Spline Models

elasticnetcran.r-project.org

Elasticnet: Elastic-Net for Sparse Estimation and Sparse PCA.

ElemStatLearncran.r-project.org

ElemStatLearn: Data sets, functions and examples from the book: "The Elements of Statistical Learning, Data Mining, Inference, and Prediction" by Trevor Hastie, Robert Tibshirani and Jerome Friedman Prediction" by Trevor Hastie, Robert Tibshirani and Jerome Friedman.

evtreecran.r-project.org

Evtree: Evolutionary Learning of Globally Optimal Trees.

forecastHybridcran.r-project.org

ForecastHybrid: Automatic ensemble and cross validation of ARIMA, ETS, STLM, TBATS, and neural network models from the "forecast" package.

fpccran.r-project.org

Fpc: Flexible procedures for clustering.

frbscran.r-project.org Deprecated

Frbs: Fuzzy Rule-based Systems for Classification and Regression Tasks.

GAMBoostcran.r-project.org Deprecated

GAMBoost: Generalized linear and additive models by likelihood based boosting.

gamboostLSScran.r-project.org

GamboostLSS: Boosting Methods for GAMLSS.

gbmcran.r-project.org

Gbm: Generalized Boosted Regression Models.

glmnetcran.r-project.org

Glmnet: Lasso and elastic-net regularized generalized linear models.

glmpathcran.r-project.org

Glmpath: L1 Regularization Path for Generalized Linear Models and Cox Proportional Hazards Model.

GMMBoostcran.r-project.org Deprecated

GMMBoost: Likelihood-based Boosting for Generalized mixed models.

grplassocran.r-project.org

Grplasso: Fitting user specified models with Group Lasso penalty.

grpregcran.r-project.org

Grpreg: Regularization paths for regression models with grouped covariates.

hdacran.r-project.org Deprecated

Hda: Heteroscedastic Discriminant Analysis.

Introduction to Statistical Learningwww-bcf.usc.edu

ipredcran.r-project.org

Ipred: Improved Predictors.