DATA MINING Desktop Survival Guide by Graham Williams
Desktop Survival Project Home List of Figures List of Tables Data Mining Data Mining Data Mining with Rattle Introduction Data Transform Explore A Model Building Framework Unsupervised Modelling Two Class Models Multi Class Models Regression Models Text Mining Evaluation and Deployment Moving into R Troubleshooting R for the Data Miner R Data Graphics in R Understanding Data Preparing Data Building Models Evaluating Models Algorithms Apriori Bagging Bayes Classifier Boosting Cluster Analysis Conditional Trees Hierarchical Clustering K-Means K-Nearest Neighbours Linear Models Logistic Regression Neural Networks Support Vector Machines Text Mining Open Products AlphaMiner Borgelt Data Mining Suite KNime R Rattle Weka Closed Products C4.5 Clementine Equbits Foresight GhostMiner InductionEngine ODM Enterprise Miner Statistica Data Miner TreeNet Virtual Predict Appendicies Glossary Bibliography Index

Clustered Box Plot

[width=0.7]rplot-bwplot

pdf("graphics/rplot-bwplot.pdf")
mydata <- data.frame(Y = rnorm(3*1000),
                     INDFACT =rep(c("A", "B", "C"), each=1000),
                     CLUSFACT=factor(rep(c("M","F"), 1500)))
library(lattice)
trellis.device(new=FALSE, col=FALSE)
bwplot(Y ~ INDFACT | CLUSFACT, data=mydata, layout=c(2,1))
dev.off()

http://rattle.togaware.com/code/rplot-bwplot.R

Support further development through the purchase of the PDF version of the book.
Brought to you by Togaware.