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Ch08 Regression.R

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@@ -281,7 +281,7 @@ relweights <- function(fit,...){
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sub=paste("Total R-Square=", round(rsquare, digits=3)),
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...)
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return(import)
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}
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# Listing 8.17 - Applying the relweights function
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states <- as.data.frame(state.x77[,c("Murder", "Population",

Ch09 Analysis of Variance.R

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@@ -151,7 +151,7 @@ outliers
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# Listing 9.10 - Robust one-way MANOVA
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library(rrcov)
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Wilks.test(y,shelf, method="mcd")
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Wilks.test(y,shelf, method="mcd") # this can take a while
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# Listing 9.11 - A regression approach to the Anova problem

Ch17 Classification.R

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@@ -97,7 +97,7 @@ svm.perf <- table(na.omit(df.validate)$class,
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svm.perf
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# Listing 17.7 Tuning an RBF support vector machine
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# Listing 17.7 Tuning an RBF support vector machine (this can take a while)
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set.seed(1234)
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tuned <- tune.svm(class~., data=df.train,
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gamma=10^(-6:1),

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