Applies Multiclass AdaBoost.M1, SAMME and Bagging
Regularization for Semiparametric Additive Hazards Regression
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
Classification, Regression and Feature Evaluation
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...
Multivariate Adaptive Regression Splines
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
Stratified and Personalised Models Based on Model-Based Trees and Fore...
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
Breiman and Cutler's Random Forests for Classification and Regression
Shrinkage Discriminant Analysis and CAT Score Variable Selection
Data Mining Classification and Regression Methods
Wrapper of Python Library 'shap'
The SVM Path Algorithm
Sure Independence Screening
Quantile Regression Forests
Variable Selection using Random Forests
Recursively Partitioned Mixture Model
Mining Association Rules and Frequent Itemsets
Lasso and Elastic-Net Regularized Generalized Linear Models
Kernel SHAP
Multivariate Elastic Net Regression
Easily Install and Load the 'Tidymodels' Packages
Prediction Rule Ensembles
Partial Dependence Plots
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
Regularized Linear Models
Generalized Linear Mixed Model Trees
Generalized Boosted Regression Models
Pam: Prediction Analysis for Microarrays
Rule- And Instance-Based Regression Modeling
Nested Cross-Validation with 'glmnet' and 'caret'
Improved Predictors
Extreme Gradient Boosting
Light Gradient Boosting Machine
Machine Learning in R - Next Generation
Kernel-Based Machine Learning Lab
A Laboratory for Recursive Partytioning
A Toolkit for Recursive Partytioning
Bayesian Treed Gaussian Process Models
Model-Based Boosting
Plot a Model's Residuals, Response, and Partial Dependence Plots
Regularization Paths for SCAD and MCP Penalized Regression Models
Fast Best Subset Selection