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

Multiple Dot Plots

[width=0.7]rplot-trellis

# Suggested by Michael Friendly
pdf("graphics/rplot-trellis.pdf")
  library(lattice)
  data(barley)
  n <- length(levels(barley$year))
  trellis.device(new = FALSE, theme = col.whitebg())
  dotplot(variety ~ yield | site, 
    data = barley, groups = year,
    layout = c(2, 3), aspect = .5,
    xlab = "Barley Yield (bushels/acre)",
    key = list(points = Rows(trellis.par.get("superpose.symbol"),1:n),
    text = list(levels(barley$year)), columns = n))
dev.off()

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

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