Wikibooks:Collections/R & Data Mining

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R & Data MiningEdit
 R Programming
 R Programming
 R Basics
 Introduction
 Sample Session
 Manage your workspace
 Settings
 Packages
 Documentation
 Control Structures
 Working with functions
 Debugging
 Using C or Fortran
 Utilities
 Estimation utilities
 Data Management
 Data types
 Working with data frames
 Importing and exporting data
 Text Processing
 Times and Dates
 Graphics
 Graphics
 Grammar of graphics
 Publication quality output
 Publication quality ouput
 Descriptive Statistics
 Descriptive Statistics
 Mathematics
 Mathematics
 Optimization
 Probability Distributions
 Random Number Generation
 Statistical Core Methods
 Maximum Likelihood
 Method of Moments
 Bayesian Methods
 Bootstrap
 Multiple Imputation
 Nonparametric Methods
 Regression Models
 Linear Models
 Quantile Regression
 Binomial Models
 Multinomial Models
 Tobit And Selection Models
 Count Data Models
 Duration Analysis
 Time Series
 Time Series
 Factor Analysis
 Factor Analysis
 Classification
 Ordination
 Clustering
 Network Analysis
 Network Analysis
 High Performance Computing
 Profiling R code
 Parallel computing with R
 Appendix
 Sources
 Index
 Data Mining Algorithms
 Data Mining Algorithms In R
 Dimensionality Reduction
 Dimensionality Reduction
 Principal Component Analysis
 Singular Value Decomposition
 Feature Selection
 Frequent Pattern Mining
 Frequent Pattern Mining
 The Eclat Algorithm
 arulesNBMiner
 The Apriori Algorithm
 The FPGrowth Algorithm
 Sequence Mining
 Sequence Mining
 SPADE
 DEGSeq
 Clustering
 Clustering
 KMeans
 Hybrid Hierarchical Clustering
 Expectation Maximization (EM)
 Dissimilarity Matrix Calculation
 Hierarchical Clustering
 DensityBased Clustering
 KCores
 Fuzzy Clustering  Fuzzy Cmeans
 RockCluster
 Biclust
 Partitioning Around Medoids (PAM)
 CLUES
 SelfOrganizing Maps (SOM)
 Proximus
 CLARA
 Classification
 Classification
 SVM
 penalizedSVM
 kNN
 Outliers
 Decision Trees
 Naïve Bayes
 adaboost
 JRip
 R Packages
 R Packages
 RWeka
 gausspred
 optimsimplex
 CCMtools
 FactoMineR
 nnet