Machine Learning & Statistical Learning - CRAN Task View

Applies Multiclass AdaBoost.M1, SAMME and Bagging

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

Bayesian Additive Regression Trees

Bayesian Additive Regression Trees

Bayesian Additive Regression Trees

Wrapper Algorithm for All Relevant Feature Selection

Gradient Boosting

C5.0 Decision Trees and Rule-Based Models

Classification and Regression Training

Deep Learning Toolkit in R

moDel Agnostic Language for Exploration and eXplanation

Fast Approximate Shapley Values

Evolutionary Learning of Globally Optimal Trees

Quick and Easy Machine Learning Tools

Depth Importance in Precision Medicine (DIPM) Method

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

Effect Displays for Linear, Generalized Linear, and Other Models

Elastic-Net for Sparse Estimation and Sparse PCA

Evidential Distance-Based Classification

Fuzzy Rule-Based Systems for Classification and Regression Tasks

Boosting Methods for 'GAMLSS'

Generalized Random Forests

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

Likelihood-Based Boosting for Generalized Mixed Models

R Interface for the 'H2O' Scalable Machine Learning Platform

Fitting User-Specified Models with Group Lasso Penalty

Regularization Paths for Regression Models with Grouped Covariates

Heteroscedastic Discriminant Analysis

High-Dimensional Inference

High-Dimensional Metrics

Model Agnostic Instance Level Variable Attributions

Individual Conditional Expectation Plot Toolbox

Interpretable Machine Learning

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

The Induced Smoothed Lasso

Classification and Visualization

Least Angle Regression, Lasso and Forward Stagewise

Feed-Forward Neural Networks and Multinomial Log-Linear Models

SHAP Visualizations

Mapping, Pruning, and Graphing Tree Models

Local Interpretable Model-Agnostic Explanations

High Performance Implementation of the Naive Bayes Algorithm

Qualitative Interaction Trees

One Rule Machine Learning Classification Algorithm with Enhancements

OPUS Miner Algorithm for Filtered Top-k Association Discovery

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

Pathwise Calibrated Sparse Shooting Algorithm

R Interface to 'TensorFlow'

Recursive Partitioning for Structural Equation Models

Visualizing the Performance of Scoring Classifiers

Super Learner Prediction

Data Analysis Using Rough Set and Fuzzy Rough Set Theories

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

R Version of GENetic Optimization Using Derivatives

Recursive Partitioning and Regression Trees

Neural Networks using the Stuttgart Neural Network Simulator (SNNS)

A Fast Implementation of Random Forests

Bayesian Structure Learning in Graphical Models using Birth-Death MCMC

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

Tools for Data Splitting

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

Prediction Explanation with Dependence-Aware Shapley Values

Reinforcement Learning Trees

R/Weka Interface

Transformation Trees and Forests

Classification and Regression Trees

Weighted Subspace Random Forest for Classification

Bayesian Graph Structure Learning using Spike-and-Slab Priors

Regularized Greedy Forest

Shrinkage Discriminant Analysis and CAT Score Variable Selection

Wrapper of Python Library 'shap'

The SVM Path Algorithm

Sure Independence Screening

Variable Selection using Random Forests

Recursively Partitioned Mixture Model

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

Mining Association Rules and Frequent Itemsets

Lasso and Elastic-Net Regularized Generalized Linear Models

Kernel SHAP

Easily Install and Load the 'Tidymodels' Packages

Breiman and Cutlers Random Forests for Classification and Regression

Prediction Rule Ensembles

Stability Selection with Error Control

Double Machine Learning in R

'Rcpp' Integration for the 'mlpack' Library

Tensors and Neural Networks with 'GPU' Acceleration

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

Evidential Regression

Penalised Multivariate Regression ('Multi-Target Learning')

Regularized Linear Models

Generalized Boosted Regression Models

Pam: Prediction Analysis for Microarrays

Rule- And Instance-Based Regression Modeling

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

Multivariate Adaptive Regression Splines

Quantile Regression Forests

Improved Predictors

Extreme Gradient Boosting

Light Gradient Boosting Machine

Kernel-Based Machine Learning Lab

A Laboratory for Recursive Partytioning

A Toolkit for Recursive Partytioning

Bayesian Treed Gaussian Process Models

Machine Learning in R - Next Generation

Model-Based Boosting

Partial Dependence Plots

Data Mining Classification and Regression Methods

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

Regularization for Semiparametric Additive Hazards Regression

Classification, Regression and Feature Evaluation

Regularization Paths for SCAD and MCP Penalized Regression Models

Generalized Linear Mixed Model Trees

Generalized Kernel Regularized Least Squares

Fast Best Subset Selection