AnomalyDetection - AnomalyDetection R package from Twitter.
ahaz - Regularization for semiparametric additive hazards regression.
arules - Mining Association Rules and Frequent Itemsets
bigrf - Big Random Forests: Classification and Regression Forests for Large Data Sets
bigRR - Generalized Ridge Regression (with special advantage for p » n cases)
bmrm - Bundle Methods for Regularized Risk Minimization Package
Boruta - A wrapper algorithm for all-relevant feature selection
BreakoutDetection - Breakout Detection via Robust E-Statistics from Twitter.
bst - Gradient Boosting
CausalImpact - Causal inference using Bayesian structural time-series models.
C50 - C5.0 Decision Trees and Rule-Based Models
caret - Classification and Regression Training
Clever Algorithms For Machine Learning
CORElearn - Classification, regression, feature evaluation and ordinal evaluation
CoxBoost - Cox models by likelihood based boosting for a single survival endpoint or competing risks
Cubist - Rule- and Instance-Based Regression Modeling
e1071 - Misc Functions of the Department of Statistics (e1071), TU Wien
earth - Multivariate Adaptive Regression Spline Models
elasticnet - Elastic-Net for Sparse Estimation and Sparse PCA
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
evtree - Evolutionary Learning of Globally Optimal Trees
FSelector - A feature selection framework, based on subset-search or feature ranking approches.
frbs - Fuzzy Rule-based Systems for Classification and Regression Tasks
GAMBoost - Generalized linear and additive models by likelihood based boosting
gamboostLSS - Boosting Methods for GAMLSS
gbm - Generalized Boosted Regression Models
glmnet - Lasso and elastic-net regularized generalized linear models
glmpath - L1 Regularization Path for Generalized Linear Models and Cox Proportional Hazards Model
GMMBoost - Likelihood-based Boosting for Generalized mixed models
grplasso - Fitting user specified models with Group Lasso penalty
grpreg - Regularization paths for regression models with grouped covariates
h2o - Deeplearning, Random forests, GBM, KMeans, PCA, GLM
hda - Heteroscedastic Discriminant Analysis
ipred - Improved Predictors
kernlab - kernlab: Kernel-based Machine Learning Lab
klaR - Classification and visualization
kohonen - Supervised and Unsupervised Self-Organising Maps.
lars - Least Angle Regression, Lasso and Forward Stagewise
lasso2 - L1 constrained estimation aka 『lasso』
LiblineaR - Linear Predictive Models Based On The Liblinear C/C++ Library
LogicReg - Logic Regression
maptree - Mapping, pruning, and graphing tree models
mboost - Model-Based Boosting
Machine Learning For Hackers
mvpart - Multivariate partitioning
MXNet - MXNet brings flexible and efficient GPU computing and state-of-art deep learning to R.
ncvreg - Regularization paths for SCAD- and MCP-penalized regression models
nnet - eed-forward Neural Networks and Multinomial Log-Linear Models
oblique.tree - Oblique Trees for Classification Data
pamr - Pam: prediction analysis for microarrays
party - A Laboratory for Recursive Partytioning
partykit - A Toolkit for Recursive Partytioning
penalized - L1 (lasso and fused lasso) and L2 (ridge) penalized estimation in GLMs and in the Cox model
penalizedLDA - Penalized classification using Fisher’s linear discriminant
penalizedSVM - Feature Selection SVM using penalty functions
quantregForest - quantregForest: Quantile Regression Forests
randomForest - randomForest: Breiman and Cutler’s random forests for classification and regression.
randomForestSRC - randomForestSRC: Random Forests for Survival, Regression and Classification (RF-SRC).
rattle - Graphical user interface for data mining in R.
rda - Shrunken Centroids Regularized Discriminant Analysis
rdetools - Relevant Dimension Estimation (RDE) in Feature Spaces
REEMtree - Regression Trees with Random Effects for Longitudinal (Panel) Data
relaxo - Relaxed Lasso
rgenoud - R version of GENetic Optimization Using Derivatives
rgp - R genetic programming framework
Rmalschains - Continuous Optimization using Memetic Algorithms with Local Search Chains (MA-LS-Chains) in R
rminer - Simpler use of data mining methods (e.g. NN and SVM) in classification and regression
ROCR - Visualizing the performance of scoring classifiers
RoughSets - Data Analysis Using Rough Set and Fuzzy Rough Set Theories
rpart - Recursive Partitioning and Regression Trees
RPMM - Recursively Partitioned Mixture Model
RSNNS - Neural Networks in R using the Stuttgart Neural Network Simulator (SNNS)
RWeka - R/Weka interface
RXshrink - RXshrink: Maximum Likelihood Shrinkage via Generalized Ridge or Least Angle Regression
sda - Shrinkage Discriminant Analysis and CAT Score Variable Selection
SDDA - Stepwise Diagonal Discriminant Analysis
SuperLearner and subsemble - Multi-algorithm ensemble learning packages.
svmpath - svmpath: the SVM Path algorithm
tgp - Bayesian treed Gaussian process models
tree - Classification and regression trees
varSelRF - Variable selection using random forests
xgboost - eXtreme Gradient Boosting Tree model, well known for its speed and performance.