85 lines
3.2 KiB
Plaintext
85 lines
3.2 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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> # Treble test for class trees with 2 outcomes
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> #
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> # fit1 and fit1b failed equality because .7 and .3 are not easily represented
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> # in binary. Thus a complelxity param was 4e-17 (basically 0, but enough
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> # to cause a split where it shouldn't be). Eric Lunde 2005-08-03
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> library(rpart)
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> control <- rpart.control(maxsurrogate=0, cp=1e-15, xval=0)
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> set.seed(10)
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>
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> fit1 <- rpart(Kyphosis ~ Age + Number + Start, data=kyphosis,
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+ control=control,
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+ parms=list(prior=c(.7,.3),
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+ loss=matrix(c(0,1,2,0),nrow=2,ncol=2)))
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> wts <- rep(3, nrow(kyphosis))
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> fit1b <- rpart(Kyphosis ~ Age + Number + Start, data=kyphosis,
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+ control=control,
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+ weights=wts,
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+ parms=list(prior=c(.7,.3),
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+ loss=matrix(c(0,1,2,0),nrow=2,ncol=2)))
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> fit1b$frame$wt <- fit1b$frame$wt/3
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> fit1b$frame$dev <- fit1b$frame$dev/3
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> fit1b$frame$yval2[,2:3] <- fit1b$frame$yval2[,2:3]/3
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> fit1b$splits[,3] <- fit1b$splits[,3]/3
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> fit1b$variable.importance <- fit1b$variable.importance/3
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> all.equal(fit1[-3], fit1b[-3]) #all but the "call"
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[1] TRUE
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>
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> # Now for a set of non-equal weights
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> nn <- nrow(kyphosis)
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> pseudo <- double(nn)
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> pseudo[1] <- pi/6
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> for (i in 2:nn) pseudo[i] <- 4*pseudo[i-1]*(1-pseudo[i-1])
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>
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> wts <- rep(1:7, length=nn)
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> temp <- rep(1:nn, wts) #row replicates
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> xgrp <- rep(1:10, length=nn)[order(pseudo)]
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> xgrp2<- rep(xgrp, wts)
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>
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> # The cp value stops one last split where the two predictors are
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> # completely equal in importance (perfect surrogates), but the
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> # weighted and unweighted pick a different one due to round off error
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> tempc <- rpart.control(minsplit=2, xval=xgrp2, maxsurrogate=0, cp=.039)
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> # Direct: replicate rows in the data set, and use unweighted
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> fit2 <- rpart(Kyphosis ~ Age + Number + Start, data=kyphosis[temp,],
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+ control=tempc,
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+ parms=list(prior=c(.7,.3),
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+ loss=matrix(c(0,1,2,0),nrow=2,ncol=2)))
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> # Weighted
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> tempc <- rpart.control(minsplit=2, xval=xgrp, maxsurrogate=0, cp=.039)
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> fit2b <- rpart(Kyphosis ~ Age + Number + Start, data=kyphosis,
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+ control=tempc, weights=wts,
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+ parms=list(prior=c(.7,.3),
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+ loss=matrix(c(0,1,2,0),nrow=2,ncol=2)))
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>
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> all.equal(fit2$frame[,-2], fit2b$frame[,-2]) # the "n" component won't match
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[1] TRUE
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> all.equal(fit2$cptable, fit2b$cptable)
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[1] TRUE
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> all.equal(fit2$splits[,-1],fit2b$splits[,-1])
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[1] TRUE
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> all.equal(fit2$csplit, fit2b$csplit)
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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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0.130 0.020 0.144
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