Machine Learning & Statistical Learning - CRAN Task View

adabag

Applies Multiclass AdaBoost.M1, SAMME and Bagging

Version 5.0

ahaz

Regularization for Semiparametric Additive Hazards Regression

Version 1.15

ALEPlot

Accumulated Local Effects (ALE) Plots and Partial Dependence (PD) Plot...

Version 1.1

ipred

Improved Predictors

Version 0.9-14

bartMachine

Bayesian Additive Regression Trees

Version 1.3.4.1

BART

Bayesian Additive Regression Trees

Version 2.9.9

BayesTree

Bayesian Additive Regression Trees

Version 0.3-1.5

BDgraph

Bayesian Structure Learning in Graphical Models using Birth-Death MCMC

Version 2.72

Boruta

Wrapper Algorithm for All Relevant Feature Selection

Version 8.0.0

bst

Gradient Boosting

Version 0.3-24

C50

C5.0 Decision Trees and Rule-Based Models

Version 0.1.8

caret

Classification and Regression Training

Version 6.0-94

deepnet

Deep Learning Toolkit in R

Version 0.2.1

CORElearn

Classification, Regression and Feature Evaluation

Version 1.57.3

DALEX

moDel Agnostic Language for Exploration and eXplanation

Version 2.4.3

fastshap

Fast Approximate Shapley Values

Version 0.1.1

evtree

Evolutionary Learning of Globally Optimal Trees

Version 1.0-8

qeML

Quick and Easy Machine Learning Tools

Version 1.1

LiblineaR

Linear Predictive Models Based on the LIBLINEAR C/C++ Library

Version 2.10-23

dipm

Depth Importance in Precision Medicine (DIPM) Method

Version 1.9

e1071

Misc Functions of the Department of Statistics, Probability Theory Gro...

Version 1.7-14

earth

Multivariate Adaptive Regression Splines

Version 5.3.3

effects

Effect Displays for Linear, Generalized Linear, and Other Models

Version 4.2-2

elasticnet

Elastic-Net for Sparse Estimation and Sparse PCA

Version 1.3

evclass

Evidential Distance-Based Classification

Version 2.0.2

frbs

Fuzzy Rule-Based Systems for Classification and Regression Tasks

Version 3.2-0

gamboostLSS

Boosting Methods for 'GAMLSS'

Version 2.0-7

grf

Generalized Random Forests

Version 2.3.2

glmpath

L1 Regularization Path for Generalized Linear Models and Cox Proportio...

Version 0.98

GMMBoost

Likelihood-Based Boosting for Generalized Mixed Models

Version 1.1.5

h2o

R Interface for the 'H2O' Scalable Machine Learning Platform

Version 3.44.0.3

grplasso

Fitting User-Specified Models with Group Lasso Penalty

Version 0.4-7

grpreg

Regularization Paths for Regression Models with Grouped Covariates

Version 3.4.0

hda

Heteroscedastic Discriminant Analysis

Version 0.2-14

hdi

High-Dimensional Inference

Version 0.1-9

hdm

High-Dimensional Metrics

Version 0.3.2

iBreakDown

Model Agnostic Instance Level Variable Attributions

Version 2.1.2

ICEbox

Individual Conditional Expectation Plot Toolbox

Version 1.1.5

iml

Interpretable Machine Learning

Version 0.11.3

kernlab

Kernel-Based Machine Learning Lab

Version 0.9-32

islasso

The Induced Smoothed Lasso

Version 1.5.2

klaR

Classification and Visualization

Version 1.7-3

lars

Least Angle Regression, Lasso and Forward Stagewise

Version 1.3

nnet

Feed-Forward Neural Networks and Multinomial Log-Linear Models

Version 7.3-19

maptree

Mapping, Pruning, and Graphing Tree Models

Version 1.4-8

mboost

Model-Based Boosting

Version 2.9-10

model4you

Stratified and Personalised Models Based on Model-Based Trees and Fore...

Version 0.9-7

lime

Local Interpretable Model-Agnostic Explanations

Version 0.5.3

naivebayes

High Performance Implementation of the Naive Bayes Algorithm

Version 1.0.0

quint

Qualitative Interaction Trees

Version 2.2.2

OneR

One Rule Machine Learning Classification Algorithm with Enhancements

Version 2.2

opusminer

OPUS Miner Algorithm for Filtered Top-k Association Discovery

Version 0.1-1

party

A Laboratory for Recursive Partytioning

Version 1.3-15

partykit

A Toolkit for Recursive Partytioning

Version 1.2-20

penalized

L1 (Lasso and Fused Lasso) and L2 (Ridge) Penalized Estimation in GLMs...

Version 0.9-52

picasso

Pathwise Calibrated Sparse Shooting Algorithm

Version 1.3.1

plotmo

Plot a Model's Residuals, Response, and Partial Dependence Plots

Version 3.6.3

tensorflow

R Interface to 'TensorFlow'

Version 2.16.0

semtree

Recursive Partitioning for Structural Equation Models

Version 0.9.20

ROCR

Visualizing the Performance of Scoring Classifiers

Version 1.0-11

SuperLearner

Super Learner Prediction

Version 2.0-29

xgboost

Extreme Gradient Boosting

Version 1.7.7.1

tgp

Bayesian Treed Gaussian Process Models

Version 2.4-22

RoughSets

Data Analysis Using Rough Set and Fuzzy Rough Set Theories

Version 1.3-8

Rborist

Extensible, Parallelizable Implementation of the Random Forest Algorit...

Version 0.3-7

shapviz

SHAP Visualizations

Version 0.9.3

rgenoud

R Version of GENetic Optimization Using Derivatives

Version 5.9-0.10

rpart

Recursive Partitioning and Regression Trees

Version 4.1.23

RSNNS

Neural Networks using the Stuttgart Neural Network Simulator (SNNS)

Version 0.4-17

ranger

A Fast Implementation of Random Forests

Version 0.16.0

RXshrink

Maximum Likelihood Shrinkage using Generalized Ridge or Least Angle Re...

Version 2.3

splitTools

Tools for Data Splitting

Version 1.0.1

Rmalschains

Continuous Optimization using Memetic Algorithms with Local Search Cha...

Version 0.2-10

shapr

Prediction Explanation with Dependence-Aware Shapley Values

Version 0.2.2

RLT

Reinforcement Learning Trees

Version 3.2.6

RWeka

R/Weka Interface

Version 0.4-46

trtf

Transformation Trees and Forests

Version 0.4-2

tree

Classification and Regression Trees

Version 1.0-43

wsrf

Weighted Subspace Random Forest for Classification

Version 1.7.30

ssgraph

Bayesian Graph Structure Learning using Spike-and-Slab Priors

Version 1.15

RGF

Regularized Greedy Forest

Version 1.1.1

randomForest

Breiman and Cutler's Random Forests for Classification and Regression

Version 4.7-1.1

sda

Shrinkage Discriminant Analysis and CAT Score Variable Selection

Version 1.3.8

rminer

Data Mining Classification and Regression Methods

Version 1.4.6

shapper

Wrapper of Python Library 'shap'

Version 0.1.3

svmpath

The SVM Path Algorithm

Version 0.970

SIS

Sure Independence Screening

Version 0.8-8

quantregForest

Quantile Regression Forests

Version 1.3-7

varSelRF

Variable Selection using Random Forests

Version 0.7-8

RPMM

Recursively Partitioned Mixture Model

Version 1.25

arules

Mining Association Rules and Frequent Itemsets

Version 1.7-7

glmnet

Lasso and Elastic-Net Regularized Generalized Linear Models

Version 4.1-8

kernelshap

Kernel SHAP

Version 0.6.0

joinet

Multivariate Elastic Net Regression

Version 0.0.10

ncvreg

Regularization Paths for SCAD and MCP Penalized Regression Models

Version 3.14.2

tidymodels

Easily Install and Load the 'Tidymodels' Packages

Version 1.2.0

pre

Prediction Rule Ensembles

Version 1.0.7

pdp

Partial Dependence Plots

Version 0.8.1

stabs

Stability Selection with Error Control

Version 0.6-4

abess

Fast Best Subset Selection

Version 0.4.8

lightgbm

Light Gradient Boosting Machine

Version 4.4.0

DoubleML

Double Machine Learning in R

Version 1.0.1

mlpack

'Rcpp' Integration for the 'mlpack' Library

Version 4.4.0

torch

Tensors and Neural Networks with 'GPU' Acceleration

Version 0.13.0

randomForestSRC

Fast Unified Random Forests for Survival, Regression, and Classificati...

Version 3.3.0

evreg

Evidential Regression

Version 1.1.1

mpath

Regularized Linear Models

Version 0.4-2.26

glmertree

Generalized Linear Mixed Model Trees

Version 0.2-5

gbm

Generalized Boosted Regression Models

Version 2.2.2

mlr3

Machine Learning in R - Next Generation

Version 0.20.0

pamr

Pam: Prediction Analysis for Microarrays

Version 1.57

Cubist

Rule- And Instance-Based Regression Modeling

Version 0.4.4

nestedcv

Nested Cross-Validation with 'glmnet' and 'caret'

Version 0.7.9