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

Other Examples

# Based on code from demo(ROCR)
library(ROCR)
data(ROCR.hiv)
  pp <- ROCR.hiv$hiv.svm$predictions
  ll <- ROCR.hiv$hiv.svm$labels
  pred <- prediction(pp, ll)
  perf <- performance(pred, "tpr", "fpr")
pdf("graphics/rplot-rocr-4plots.pdf")
  par(mfrow = c(2, 2))
  plot(perf, avg = "threshold", colorize = T, lwd = 3,
       main = "Standard ROC curve.")

  plot(perf, lty = 3, col = "grey78", add = T)
  perf <- performance(pred, "prec", "rec")
  plot(perf, avg = "threshold", colorize = T, lwd = 3,
       main = "Precision/Recall graph.")

  plot(perf, lty = 3, col = "grey78", add = T)
  perf <- performance(pred, "sens", "spec")
  plot(perf, avg = "threshold", colorize = T, lwd = 3,
       main = "Sensitivity/Specificity plot.")

  plot(perf, lty = 3, col = "grey78", add = T)
  perf <- performance(pred, "lift", "rpp")
  plot(perf, avg = "threshold", colorize = T, lwd = 3,
    main = "Lift chart.")

  plot(perf, lty = 3, col = "grey78", add = T)
dev.off()

http://rattle.togaware.com/code/rplot-rocr-4plots.R

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