gistfile1.txt

training_comp<-training%>%na.omit()
enetgrid<-expand.grid(.lambda=c(0,0.01,.1),
                      .fraction = seq(0.5, 1 , length=20))
enet1 <- train(rochefant~.-customer, data = training_comp, 
               preProcess = c("center", "scale"),
               method = "enet", 
               tuneGrid=enetgrid,
               trControl = tr)
enet1;summary(enet1);plot(enet1)
enet1pred<-predict(enet1, testing)
pm1values<-data.frame(obs=testing$rochefant, 
                      pred=enet1pred, 
                      wts=testing$weightclasshalv, 
                      cfactor=testing$c.factor,
                      length=testing$length)
ggplot(pm1values, aes(obs,pred, 
                      colour=length, 
                      size=cfactor)) +
  geom_point(alpha=0.3,size=2) +
  geom_smooth(method=lm, se=FALSE,colour="red", linetype="dashed")+
  geom_abline(slope=1, linetype="dashed") + theme_bw() +
  facet_wrap(~wts)