User:Waldyd/Collections/R & Data Mining

R & Data Mining

 * 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 FP-Growth Algorithm


 * Sequence Mining
 * Sequence Mining
 * SPADE
 * DEGSeq


 * Clustering
 * Clustering
 * K-Means
 * Hybrid Hierarchical Clustering
 * Expectation Maximization (EM)
 * Dissimilarity Matrix Calculation
 * Hierarchical Clustering
 * Density-Based Clustering
 * K-Cores
 * Fuzzy Clustering - Fuzzy C-means
 * RockCluster
 * Biclust
 * Partitioning Around Medoids (PAM)
 * CLUES
 * Self-Organizing 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