# ****************************************************************
# Lababoratorio 22: Regresion usando arboles de decision
# Usa la libreria tree de Ripley
# Mayo 2003, Edgar Acuna
#****************************************************************
library(tree)
  arbol<-tree(ozone~radiation+temperature,data=air)
  arbol
 summary(arbol)
  win.graph()
 plot.tree(arbol, type="u")
  text(arbol)
mejorarbol<-prune.tree(arbol,best=5)
  mejorarbol
win.graph()
  plot.tree(mejorarbol, type="u")
  text(mejorarbol)
gtemp<-seq(min(air$temperature),max(air$temperature),length=50)
 gradiation<-seq(min(air$radiation),max(air$radiation),length=50)
 grid<-cbind(gtemp,gradiation)
 grid1<-list(radiation=gradiation,temperature=gtemp)
 grid1<-expand.grid(grid1)
 estimado<-predict.tree(arbol,grid1)
  grid2<-as.data.frame(grid1)
  matest<-matrix(estimado,50,50)
  persp(gradiation,gtemp,matest, theta=30, phi=45, xlab="radiation", ylab="temperature", zlab="ozone")