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

Probability Scale

[width=0.8]rplot-proby

pdf("graphics/rplot-proby.pdf")
  x <- sort(rnorm(100))
  y <- 0.5+(0:99)
  p <- c(0.01, 0.05, 0.5, 0.95, 0.99)
  qqplot(x, qnorm(0.005+0.01*(0:99)), yaxt="n")
  axis(2, at=qnorm(p), label=p, las=1)
dev.off()

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

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