# przyklad 6.6

options(OutDec=",")
library("ElemStatLearn")
library("mlbench")
library("rpart")
library("adabag") tu jest bagging
library("gbm")

data(cpus)

cpus2<-cpus[,-9]
cpus2<-cpus2[,-1]
cpus2$perf<-log10(cpus2$perf)

m<-nrow(cpus2)

test <- sample(1:m, size = m/3, replace = FALSE) 
cpus2.ucz<-cpus2[-test,]
cpus2.test<-cpus2[test,]

lzm<-ncol(cpus2)-1

gbm.cpus<-gbm(perf~ .,data=cpus2,var.monotone=c(-1,1,1,1,1,1), distribution="gaussian",
n.trees=1000,interaction.depth=1,train.fraction = 2/3,cv.folds = 10)

best.iter <- gbm.perf(gbm.cpus,method="OOB")
print(best.iter)

cc<-gbm.perf(gbm.cpus,plot.it = TRUE, oobag.curve = F, overlay = TRUE, method="test")

# rys. 6.5 a
ks<-seq(1,1000,1)
a<-gbm.cpus$valid.error
b<-gbm.cpus$train.error
plot(ks,a,type="n",ylim=c(min(a,b),max(a,b)),main="Zbiór Cpus",ylab="MSE",xlab="Liczba modeli bazowych")
lines(ks,a,lty=1)
lines(ks,b,lty=2)
legend("topright",lty=c(1,2),legend = c("zbiór testowy","zbiór uczący"))


# rys. 6.5b
plot(gbm.cpus,i.var = 1,continuous.resolution = best.iter,return.grid = F,main="Zbiór CPUS")