105 lines
2.4 KiB
R
105 lines
2.4 KiB
R
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#-*- R -*-
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## Script from Fourth Edition of `Modern Applied Statistics with S'
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# Chapter 9 Tree-based Methods
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library(MASS)
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pdf(file="ch09.pdf", width=8, height=6, pointsize=9)
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options(digits=5)
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library(rpart)
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# Figure 9.3
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shuttle.rp <- rpart(use ~ ., data=shuttle, minbucket=0, xval = 0,
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maxsurrogate = 0, cp = 0, subset = 1:253)
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post(shuttle.rp, horizontal = FALSE, height=10, width=8, title = "",
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pointsize = 8, pretty = 0)
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# 9.3 Implementation in rpart
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set.seed(123)
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cpus.rp <- rpart(log10(perf) ~ ., cpus[ , 2:8], cp = 1e-3)
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cpus.rp
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print(cpus.rp, cp = 0.01) # default pruning
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plot(cpus.rp, uniform = TRUE)
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text(cpus.rp, digits = 3)
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printcp(cpus.rp)
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plotcp(cpus.rp)
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cpus.rp1 <- prune(cpus.rp, cp = 0.006)
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print(cpus.rp1, digits = 3)
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plot(cpus.rp1, branch = 0.4, uniform = TRUE)
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text(cpus.rp1, digits = 3)
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# for figure 9.2
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cpus.rp2 <- prune(cpus.rp, cp = 0.03)
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post(cpus.rp2, horizontal = FALSE, title = "", digits=4, pointsize=18)
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set.seed(123)
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fgl.rp <- rpart(type ~ ., fgl, cp = 0.001)
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plotcp(fgl.rp)
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printcp(fgl.rp)
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fgl.rp2 <- prune(fgl.rp, cp = 0.02)
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plot(fgl.rp2, uniform = TRUE)
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text(fgl.rp2, use.n = TRUE)
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fgl.rp2
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summary(fgl.rp2)
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set.seed(123)
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fgl.rp3 <- rpart(type ~ ., fgl, cp = 0.001,
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parms = list(split="information"))
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plotcp(fgl.rp3)
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printcp(fgl.rp3)
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fgl.rp4 <- prune(fgl.rp3, cp = 0.03)
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plot(fgl.rp4, uniform = TRUE); text(fgl.rp4, use.n = TRUE)
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plot(cpus.rp, branch = 0.6, compress = TRUE, uniform = TRUE)
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text(cpus.rp, digits = 3, all = TRUE, use.n = TRUE)
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# 9.3 Implementation in tree
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library(tree)
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## the stopping criteria differ slightly between R and S-PLUS
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cpus.ltr <- tree(log10(perf) ~ ., data = cpus[, 2:8], mindev = 0.005)
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summary(cpus.ltr)
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cpus.ltr
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plot(cpus.ltr, type="u"); text(cpus.ltr)
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par(mfrow = c(1, 2), pty = "s")
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set.seed(321)
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plot(cv.tree(cpus.ltr, , prune.tree))
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cpus.ltr1 <- prune.tree(cpus.ltr, best = 10)
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plot(cpus.ltr1, type = "u")
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text(cpus.ltr1, digits = 3)
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par(mfrow = c(1, 1), pty = "m")
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fgl.tr <- tree(type ~ ., fgl)
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summary(fgl.tr)
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plot(fgl.tr)
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text(fgl.tr, all = TRUE, cex = 0.5)
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par(mfrow = c(1, 2), pty = "s")
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set.seed(123)
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fgl.cv <- cv.tree(fgl.tr,, prune.misclass)
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for(i in 2:5) fgl.cv$dev <- fgl.cv$dev +
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cv.tree(fgl.tr,, prune.misclass)$dev
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fgl.cv$dev <- fgl.cv$dev/5
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fgl.cv
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plot(fgl.cv)
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fgl.tr1 <- prune.misclass(fgl.tr, best = 9)
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plot(fgl.tr1, type = "u")
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text(fgl.tr1, all = TRUE)
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# End of ch09
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