inst/scripts/Nonlinear/tree.R

In gbonte/gbcode: Code from the handbook "Statistical foundations of machine learning"

## "INFOF422 Statistical foundations of machine learning" course
## R package gbcode 
## Author: G. Bontempi 



rm(list=ls())
source("dopler.R")
library(tree)

N<-2000
D<-dataset.dopler(2000)
plot(D$x,D$y,type="l")

d<-data.frame(D$y,D$x)
names(d)<-c("Y","X")

for (number.nodes in 1:30){
  
  mod.tree<-tree(Y~.,d,minsize=number.nodes,mindev=0)
  d.ts<-data.frame(D$y.ts,D$x.ts)
  names(d.ts)<-c("Y","X")
  p<-predict(mod.tree,d.ts)
  
  
  
  plot(D$x.ts,D$y.ts,type="l", main=paste("Min number points per leaf=",number.nodes))
  lines(D$x.ts,p,col="red")
  browser()
}