55 lines
1.8 KiB
Plaintext
55 lines
1.8 KiB
Plaintext
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R Under development (unstable) (2019-04-05 r76323) -- "Unsuffered Consequences"
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Copyright (C) 2019 The R Foundation for Statistical Computing
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Platform: x86_64-pc-linux-gnu (64-bit)
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R is free software and comes with ABSOLUTELY NO WARRANTY.
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You are welcome to redistribute it under certain conditions.
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Type 'license()' or 'licence()' for distribution details.
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R is a collaborative project with many contributors.
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Type 'contributors()' for more information and
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'citation()' on how to cite R or R packages in publications.
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Type 'demo()' for some demos, 'help()' for on-line help, or
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'help.start()' for an HTML browser interface to help.
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Type 'q()' to quit R.
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> #
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> # Test out the "return.all" argument of xpred
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> # this is a very small test case for debugging
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> #
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> library(rpart)
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> set.seed(10)
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>
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> tdata <- data.frame(y=1:12, x1= 12:1, x2=c(1,1,5,5,4,4,9,9,7,7,3,3))
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> xgrp <- rep(1:3, length=12)
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>
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> fit1 <- rpart(y ~ x1 + x2, tdata, minsplit=6)
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> xfit1 <- xpred.rpart(fit1, xval=xgrp, return.all=T)
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>
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> xfit2 <- array(0, dim=dim(xfit1))
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> cplist <- as.numeric(dimnames(xfit1)[[2]])
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>
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> for (i in 1:3) {
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+ tfit <- rpart(y ~ x1+x2, tdata, subset=(xgrp !=i), minsplit=6)
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+ # xvals are actually done on the absolute risk (node's risk /n), not on
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+ # the rescaled risk ((node risk)/ (top node risk)) which is the basis
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+ # for the printed CP. To get the right answer we need to rescale.
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+ cp2 <- cplist * (fit1$frame$dev[1] / fit1$frame$n[1]) /
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+ (tfit$frame$dev[1] / tfit$frame$n[1])
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+
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+ for (j in 1:length(cp2)) {
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+ tfit2 <- prune(tfit, cp=cp2[j])
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+ temp <- predict(tfit2, newdata=tdata[xgrp==i,], type='matrix')
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+ xfit2[xgrp==i, j] <- temp
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+ }
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+ }
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>
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> all.equal(xfit1, xfit2, check.attributes=FALSE)
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[1] TRUE
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>
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> proc.time()
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user system elapsed
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0.141 0.015 0.151
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