Using KNN and Kmeans Together

setosa<- rbind(iris[iris$Species=="setosa",])
versicolor<- rbind(iris[iris$Species=="versicolor",])
virginica<- rbind(iris[iris$Species=="virginica",])
ind<- 1:30
iris.train<- rbind(setosa[ind,], versicolor[ind,], virginica[ind,])
iris.test<- rbind(setosa[-ind,], versicolor[-ind,], virginica[-ind,])
knn.iris<- knn(train = iris.train[, -5], test = iris.test[, -5], cl=iris.train[,5], k=5)
kmeansv<-kmeans(iris.test[,1:4],centers = 3, iter.max = 10)
value<-kmeansv$cluster
value<-as.data.frame(value)
Comp<-c(iris.test$Species,value,knn.iris)
Comp<-c(as.data.frame(iris.test$Species),as.data.frame(value),as.data.frame(knn.iris))
Comp$Kmeans<-ifelse(Comp$value==1,"setosa",ifelse(Comp$value==2,"virginica",ifelse(Comp$value==3,"versicolor",0)))
Comp$knnflag<-ifelse(Comp$knn.iris==Comp$`iris.test$Species`,0,1)
Comp$kmeanflag<-ifelse(Comp$Kmeans==Comp$`iris.test$Species`,0,1)
View(Comp)

## Error in .External2(C_dataviewer, x, title): unable to start data viewer

iris.test$knnflag<-Comp$knnflag
iris.test$kmeanflag<-Comp$kmeanflag
View(iris.test)

## Error in .External2(C_dataviewer, x, title): unable to start data viewer

p1<-ggplot(iris.test, aes(x=iris.test$Sepal.Length, y=iris.test$Sepal.Width))
p1+geom_point(aes(color=iris.test$knnflag))

p1+geom_point(aes(color=iris.test$kmeanflag))

p2<-ggplot(iris.test, aes(x=iris.test$Petal.Length, y=iris.test$Petal.Width))
p2+geom_point(aes(color=iris.test$knnflag))

p2+geom_point(aes(color=iris.test$kmeanflag))