Data Mining Algorithms In R/Print version

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Data Mining Algorithms In R

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Dimensionality Reduction

  1. Principal Component Analysis
  2. Singular Value Decomposition
  3. Feature Selection


Frequent Pattern Mining

Contents[edit | edit source]

  1. The Eclat Algorithm
  2. arulesNBMiner
  3. The Apriori Algorithm
  4. The FP-Growth Algorithm


Sequence Mining

  1. SPADE
  2. DEGSeq


Clustering

  1. K-Means
  2. Hybrid Hierarchical Clustering
  3. Expectation Maximization (EM)
  4. Dissimilarity Matrix Calculation
  5. Hierarchical Clustering
  6. Bayesian Hierarchical Clustering
  7. Density-Based Clustering
  8. K-Cores
  9. Fuzzy Clustering - Fuzzy C-means
  10. RockCluster
  11. Biclust
  12. Partitioning Around Medoids (PAM)
  13. CLUES
  14. Self-Organizing Maps (SOM)
  15. Proximus
  16. CLARA


Classification

  1. SVM
  2. penalizedSVM
  3. kNN
  4. Outliers
  5. Decision Trees
  6. Naïve Bayes
  7. adaboost
  8. JRip


R Packages

In this section, we will discuss about R packages that are related to datamining.

Contents[edit | edit source]

  1. RWeka
  2. gausspred
  3. optimsimplex
  4. CCMtools
  5. FactoMineR
  6. nnet


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