Wikibooks:Collections/R & Data Mining
Appearance
|
This is a collection of the pages in a Wikibooks book that can be easily saved, rendered electronically, and ordered as a printed book. For information and help on Wikibooks collections, see Help:Collections. | ||||||||
[ Download PDF ] [ Open in Collection Creator ] [ Order Printed Book ] | |||||||||
[ About ] [ FAQ ] [ Feedback ] [ Help ] [ Recent Changes ] |
R & Data Mining
[edit source]- 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