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#
# The treble test for classification trees
#
#
library(rpart)
set.seed(10)
xgrp <- rep(1:10,length=nrow(cu.summary))
carfit <- rpart(Country ~ Reliability + Price + Mileage + Type,
method='class', data=cu.summary,
control=rpart.control(xval=xgrp))
carfit2 <- rpart(Country ~ Reliability + Price + Mileage + Type,
method='class', data=cu.summary,
weight=rep(3,nrow(cu.summary)),
control=rpart.control(xval=xgrp))
all.equal(carfit$frame$wt, carfit2$frame$wt/3)
all.equal(carfit$frame$dev, carfit2$frame$dev/3)
all.equal(carfit$frame[,5:7], carfit2$frame[,5:7])
all.equal(carfit$frame$yval2[,12:21], carfit2$frame$yval2[,12:21])
all.equal(carfit[c('where', 'csplit')],
carfit2[c('where', 'csplit')])
xx <- carfit2$splits
xx[,'improve'] <- xx[,'improve'] / ifelse(xx[,5]> 0,1,3) # surrogate?
all.equal(xx, carfit$splits)
all.equal(as.vector(carfit$cptable),
as.vector(carfit2$cptable%*% diag(c(1,1,1,1,sqrt(3)))))
summary(carfit2)
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