R Language Common Data mining package

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The collection of R packages and functions available for data mining is listed below. Some of them are not specifically developed for data mining, but these packages can help us a lot in the process of data mining, so they are included.

1. Clustering

• Commonly used packages: Fpc,cluster,pvclust,mclust

• Partitioning-based approach: Kmeans, Pam, PAMK, Clara

• Hierarchy-based approach: Hclust, Pvclust, Agnes, Diana

• Model-based approach: Mclust

• Density-based approach: Dbscan

• Drawing-based method: Plotcluster, Plot.hclust

• Verification-based method: Cluster.stats

2. Classification

• Commonly used packages:

  Rpart,party,randomforest,rpartordinal,tree,margintree,

  Maptree,survival

• Decision Tree: Rpart, Ctree

• Random forest: Cforest, Randomforest

• Regression, logistic regression, poisson regression: GLM, predict, residuals

• Survival analysis: Survfit, Survdiff, coxph

3. Association rule and frequent item set

• Commonly used packages:

  Arules: Supports mining frequent itemsets, maximum frequent itemsets, frequent closed itemsets, and association rules

  DRM: A repetitive association model of regression and categorical data

• Apriori algorithm, breadth rst algorithm: Apriori, DRM

• Eclat algorithm: Using equivalence class, RST depth search and the intersection of sets: Eclat

4. Sequence mode

• Commonly used packages: Arulessequences

• Spade algorithm: Cspade

5. Time series

• Commonly used packages: Timsac

• Time series build function: TS

• Component decomposition: Decomp, decompose, STL, TSR

6. Statistics

• Commonly used packages: Base R, Nlme

• Variance analysis: AoV, ANOVA

• Density Analysis: Density

• Hypothesis test: T.test, Prop.test, Anova, AoV

• Linear hybrid Model: LME

• Principal component Analysis and Factor analysis: Princomp

7. Chart

• Bar chart: Barplot

• Pie chart: Pie

• Scatter chart: Dotchart

• Histogram: hist

• Density chart: Densityplot

• Candle chart, box-shaped diagram BoxPlot

• QQ (quantile-quantile) Chart: Qqnorm, Qqplot, Qqline

• Bi-variate Plot:coplot

• Tree: Rpart

• Parallel Coordinates:parallel, Paracoor, Parcoord

• Heat map, Contour:contour, Filled.contour

• Other diagrams: Stripplot, Sunflowerplot, Interaction.plot, Matplot, Fourfoldplot,
  Assocplot, Mosaicplot

• Saved Chart formats: PDF, PostScript, Win.metafile, JPEG, BMP, PNG

8. Data manipulation

• Missing value: Na.omit

• Variable Normalization: Scale

• Variable transpose: t

• Sample: Sample

• Stacks: Stack, unstack

• Others: Aggregate, merge, reshape

9. Interface with data mining software Weka

• Rweka: With this interface, all the Weka algorithms can be used in R.

R Language Common Data mining package