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1. # Classification and Regression Trees (CART)
2. library(rpart)
3. dt<-brabant[samp,]
4. attach(dt)
5. formula<-if_cde97 ~ r6 + rr6 + f6m + m6m + mm6m + caa96 + cda96
6. rfm.rpart<- rpart(formula, method="class", control=rpart.control(cp=.001))
7. #splrpart<-as.matrix(rfm.rpart$splits)
8. plot(rfm.rpart)
9. text(rfm.rpart)
10. dt<-brabant[-samp,]
11. attach(dt)
12. predictv<-predict(rfm.rpart, newdata=dt)[,2]
13. names(predictv)<-1:length(predictv)
14. gc<-gainchart(predictv,if_cde97)
15. par(mfrow=c(2,2))
16. plot_gaincharts(gc)