Chapter 10 (Computing finished)

Today, I fixed some problems of computing of Chapter 10.

Codes:
pp2=preProcess(age28data[, 1:7], "pca")
pca1=predict(pp2, age28data[, 1:7])
head(pca1)
pca1$Data="Training Set"
pca1$Data[startpoints]="Starting Values"
pca3=predict(pp2, cbresults[, 1:7])
pca3$Data="Cubist"
head(pca3)
pca4=predict(pp2, nnetresults[, 1:7])
pca4$Data="Neural Network"
head(pca4)
pcadata=rbind(pca1, pca3, pca4)
dim(pcadata)
pcadata$Data=factor(pcadata$Data,
                    levels = c("Training Set","Starting Values",
                    "Cubist","Neural Network"))
lim=extendrange(pcadata[, 1:2])

# convert a vector of strings into a vector of numbers
m=with(pcadata, as.numeric(levels(factor(as.numeric(factor(pcadata$Data))))))
m=with(pcadata, levels(factor(Data)))
m
colm=c()
for(i in 1:length(pcadata$Data))
{
  colm[i]=which(pcadata$Data[i]==m)
}
colm

xyplot(PC2 ~ PC1, data = pcadata, groups = Data,
       auto.key = list(columns = 2),
       xlim = lim, ylim = lim,
       col=colm,
       type = c("g", "p")
      )

xyplot(PC2 ~ PC1, data = pcadata, groups = Data,
       auto.key = list(columns = 2),
       xlim = lim, ylim = lim,
       col=c("blue", "pink", "red", "green"),
       type = c("g", "p")
)

Next week, I will start to look into the NMR data.