attach(olives)

library(MASS)

plot(palmitoleic, oleic, col=Region)

plot.contours2d(palmitoleic[Region==1], oleic[Region==1], clevels=0.95, label=F)
plot.contours2d(palmitoleic[Region==2], oleic[Region==2], clevels=0.95, label=F)
plot.contours2d(palmitoleic[Region==3], oleic[Region==3], clevels=0.95, label=F)

###
#
# Generate Grid for Prediction

rast.x<- rep(seq(min(palmitoleic), max(palmitoleic),length=75), 75)
rast.y<- rep(seq(min(oleic), max(oleic), length=75), rep(75, 75))

###
#
# 1. LDA

o.lda <- lda( cbind(palmitoleic, oleic), Region )

table(predict(o.lda, cbind(palmitoleic, oleic))$class, Region)

sum(diag(as.matrix(table(predict(o.lda, cbind(palmitoleic, oleic))$class, Region))))/length(Region)

pred<-predict(o.lda, cbind(rast.x, rast.y))
col<-unclass(pred$class)
points(rast.x, rast.y, col=col, pch="+")

###
#
# 2. QDA

o.qda <- qda( cbind(palmitoleic, oleic), Region )

table(predict(o.qda, cbind(palmitoleic, oleic))$class, Region)

sum(diag(as.matrix(table(predict(o.qda, cbind(palmitoleic, oleic))$class, Region))))/length(Region)

pred<-predict(o.qda, cbind(rast.x, rast.y))
col<-unclass(pred$class)
points(rast.x, rast.y, col=col, pch="+")