library(class)
library(nnet)

TrainC<-read.table("trainC.dat")
names(TrainC)<-c("x1","x2","y")

K=11

p <- as.matrix(TrainC[, -3])
xp <- seq(min(TrainC$x1), max(TrainC$x1), length = 50); np <- length(xp)
yp <- seq(min(TrainC$x2), max(TrainC$x2), length = 50)
tp<-TrainC$y

yhat <- knn(p, p, tp, k = K)

par(mfcol=c(1,2))

plot(TrainC[, 1], TrainC[, 2], xlab = "x1", ylab = "x2", col=codes(TrainC$y)+1)
pt <- expand.grid(x1 = xp, x2 = yp)
Z <- knn(p, pt, tp, k = K)
zp<-class.ind(Z)[,1] - class.ind(Z)[,2]

contour(xp, yp, matrix(zp, np), add = T, levels = 0, labex = 0)

CErr=0
for( i in 1:50 ) { if( yhat[i] == 'b' ) CErr = CErr + 1 }
for( i in 51:100 ) { if( yhat[i] == 'a' ) CErr = CErr + 1 }

title(paste("Knn(",K,") of TrainC"))
mtext(paste("Plug-in Error=",format(100*CErr/100,digits=3),"%"))

TestC <- read.table("TestC.dat")
names(TestC)<-c("x1","x2")
N <- length(TestC[,1])

yThat <- knn(p, TestC, tp, k = K)

plot(TestC[, 1], TestC[, 2], xlab = "x1", ylab = "x2", col=codes(yThat)+1)
title(paste("Knn(",K,") of TestC"))

xp <- seq(min(TestC$x1), max(TestC$x1), length = 50); np <- length(xp)
yp <- seq(min(TestC$x2), max(TestC$x2), length = 50)
pt <- expand.grid(x1 = xp, x2 = yp)

Z <- knn(p, pt, tp, k = K)
zp<-class.ind(Z)[,1] - class.ind(Z)[,2]
contour(xp, yp, matrix(zp, np), add = T, levels = 0, labex = 0)

Result<-data.frame(TestC,yThat)
write.table(Result,paste("TestC-C-KNN-",K,".dat"), quote=F, col.names=F, row.names=F)