som.nn.confusion

Calculates the confusion matrix for a prediction result
if the corresponding vector of true class labels
is provided.

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.confusion function

<dl><dt>x</dt>
<dd><code>data.frame</code> with the predictions as returned by the
SOM.nn predict method.</dd>
<dt>class.labels</dt>
<dd><code>vector</code> of correct class labels for the predictions.</dd></dl>

Arguments

Calculate confusion matrix — som.nn.confusion

<dl>

<dt>x</dt>
<dd><code>data.frame</code> with the predictions as returned by the
SOM.nn predict method.</dd>


<dt>class.labels</dt>
<dd><code>vector</code> of correct class labels for the predictions.</dd>

</dl>

	pred. cat	pred. dog	pred. rabbit	unknown
actual cat	5	3	0	0
actual dog	2	3	1	0
actual rabbit	0	2	9	2

som.nn.confusion: Calculate confusion matrix

Description

Usage

Value

Arguments

Details