som.nn.visual.one

Working hourse function for visual.

internal

A topological version of k-NN: An abstract model is build
as 2-dimensional self-organising map. Samples of unknown
class are predicted by mapping them on the SOM and analysing
class membership of neurons in the neighbourhood.

Andreas Dominik

som.nn

Topological k-NN Classifier Based on Self-Organising Maps

som.nn.visual.one function

<dl><dt>one</dt>
<dd><code>numeric</code> vector to be mapped</dd>
<dt>codes</dt>
<dd><code>numeric matrix</code> of codebook vectors with
one code per row</dd></dl>

Arguments

Maps one vector to the SOM — som.nn.visual.one

<dl>

<dt>one</dt>
<dd><code>numeric</code> vector to be mapped</dd>


<dt>codes</dt>
<dd><code>numeric matrix</code> of codebook vectors with
one code per row</dd>

</dl>

som.nn.visual.one: Maps one vector to the SOM

Description

Usage

Value

Arguments