1-nearest neighbour classification

DESCRIPTION:

Nearest neighbour classification for test set from training set. For each row of the test set, the nearest (by Euclidean distance) training set vector is found, and its classification used. If there is more than one nearest, a majority vote is used with ties broken at random.

USAGE:

knn1(train, test, cl)

REQUIRED ARGUMENTS:

train
matrix or data frame of training set cases.
test
matrix or data frame of test set cases. A vector will be interpreted as a row vector for a single case.
cl
factor of true classification of training set.

VALUE:

factor of classifications of test set.

SEE ALSO:

EXAMPLES:

train <- rbind(iris[1:25,,1],iris[1:25,,2],iris[1:25,,3])
test <- rbind(iris[26:50,,1],iris[26:50,,2],iris[26:50,,3])
cl <- factor(c(rep("s",25),rep("c",25), rep("v",25)))
knn1(train, test, cl)