. , , knn. ?knn
library(class)
train <- rbind(iris3[1:25,,1], iris3[1:25,,2], iris3[1:25,,3])
test <- rbind(iris3[26:50,,1], iris3[26:50,,2], iris3[26:50,,3])
cl <- factor(c(rep("s",25), rep("c",25), rep("v",25)))
fit <- knn(train, test, cl, k = 3, prob=TRUE)
,
head(data.frame(test, pred=fit, prob=attr(fit, "prob")))
test.