# k Nearest Neighbor Regression

### Description

k-nearest neighbor regression

### Usage

1 |

### 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. If not supplied, cross-validataion will be done. |

`y` |
reponse of each observation in the training set. |

`k` |
number of neighbours considered. |

`algorithm` |
nearest neighbor search algorithm. |

### Details

If test is not supplied, Leave one out cross-validation is performed and *R-square* is the predicted R-square.

### Value

`knn.reg`

returns an object of `class`

`"knnReg"`

or `"knnRegCV"`

if `test`

data is not supplied.

The returnedobject is a list containing at least the following components:

`call` |
the match call. |

`k` |
number of neighbours considered. |

`n` |
number of predicted values, either equals test size or train size. |

`pred` |
a vector of predicted values. |

`residuals` |
predicted residuals. |

`PRESS` |
the sums of squares of the predicted residuals. |

`R2Pred` |
predicted R-square. |

### Note

The code for “VR” nearest neighbor searching is taken from `class`

source

### Author(s)

Shengqiao Li. To report any bugs or suggestions please email: shli@stat.wvu.edu.

### See Also

`knn`

.

### Examples

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