R框架、包和软件集合：Awesome R

h2o - Deeplearning, Random forests, GBM, KMeans, PCA, GLM

Clever Algorithms For Machine Learning

Machine Learning For Hackers

rpart - Recursive Partitioning and Regression Trees

randomForest - Breiman and Cutler's random forests for classification and regression

lasso2 - L1 constrained estimation aka ‘lasso’

gbm - Generalized Boosted Regression Models

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

tgp - Bayesian treed Gaussian process models

rgp - R genetic programming framework

arules - Mining Association Rules and Frequent Itemsets

frbs - Fuzzy Rule-based Systems for Classification and Regression Tasks

rattle - Graphical user interface for data mining in R

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

bst - Gradient Boosting

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

caret - Classification and Regression Training

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

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

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

hda - Heteroscedastic Discriminant Analysis

ipred - Improved Predictors

kernlab - kernlab: Kernel-based Machine Learning Lab

klaR - Classification and visualization

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

mvpart - Multivariate partitioning

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)

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

svmpath - svmpath: the SVM Path algorithm

tgp - Bayesian treed Gaussian process models

tree - Classification and regression trees

varSelRF - Variable selection using random forests

caret - Unified interface to ~150 ML algorithms in R.

SuperLearner and subsemble - Multi-algorithm ensemble learning packages.

Introduction to Statistical Learning

Integrated Development Environment

Data Manipulation

Graphic Displays

Reproducible Research

Web Technologies and Services

Parallel Computing

High Performance

Language API

Database Management

Machine Learning

Natural Language Processing

Bayesian

Finance

Genetics

R Development

Other Interpreter

Resources

Websites

Books

Reference Card

Other Awesome Lists

相关经验

目录