# knn1: 1-Nearest Neighbour Classification In class: Functions for 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

 `1` ```knn1(train, test, cl) ```

## 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.

## References

Ripley, B. D. (1996) Pattern Recognition and Neural Networks. Cambridge.

Venables, W. N. and Ripley, B. D. (2002) Modern Applied Statistics with S. Fourth edition. Springer.

`knn`

## Examples

 ```1 2 3 4``` ```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))) knn1(train, test, cl) ```

### Example output

``` [1] s s s s s s s s s s s s s s s s s s s s s s s s s c c c c c c c c v c c c c
[39] c c c c c c c c c c c c v v c v v v v v c v v v v c v v v v v v v v v v v
Levels: c s v
```

class documentation built on Jan. 13, 2022, 9:07 a.m.