Description Usage Arguments Details Value Author(s) See Also Examples

Function for nearest mean classification.

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`x` |
matrix or data frame containing the explanatory variables
(required, if |

`grouping` |
factor specifying the class for each observation
(required, if |

`formula` |
formula of the form |

`data` |
Data frame from which variables specified in |

`gamma` |
gamma parameter for rbf weight of the distance to mean. If |

`subset` |
An index vector specifying the cases to be used in the training sample. (Note: If given, this argument must be named!) |

`na.action` |
specify the action to be taken if |

`...` |
further arguments passed to the underlying |

`nm`

is calling `sknn`

with the class means as observations.
If `gamma>0`

a gaussian like density is used to weight the distance to the class means
`weight=exp(-gamma*distance)`

. This is similar to an rbf kernel.
If the distances are large it may be useful to `scale`

the data first.

A list containing the function call and the class means (`learn`

)).

Karsten Luebke, karsten.luebke@fom.de

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