iUstarmatrix

Calculates the Ustarmatrix by combining a Umatrix with a Pmatrix.

By gaining the property of emergence through self-organization, the enhancement of SOMs(self organizing maps) is called Emergent SOM (ESOM). The result of the projection by ESOM is a grid of neurons which can be visualised as a three dimensional landscape in form of the Umatrix. Further details can be found in the referenced publications (see url). This package offers tools for calculating and visualising the ESOM as well as Umatrix, Pmatrix and UStarMatrix. All the functionality is also available through graphical user interfaces implemented in 'shiny'. Based on the recognized data structures, the method can be used to generate new data.

Jorn Lotsch

Umatrix

Visualization of Structures in High-Dimensional Data

iUstarmatrix function

<dl> <dt>Weights</dt>
<dd>Weights that were trained by the ESOM algorithm</dd> <dt>Lines</dt>
<dd>Height of the used grid</dd> <dt>Columns</dt>
<dd>Width of the used grid</dd> <dt>Data</dt>
<dd>Matrix of Data that was used to train the ESOM. One datapoint per row</dd> <dt>Imx</dt>
<dd>Island mask that will be cut out from displayed Umatrix</dd> <dt>Cls</dt>
<dd>Classification of the Bestmatches</dd> <dt>Toroid</dt>
<dd>Are weights placed on a toroid grid?</dd></dl>

Arguments

iUstarmatrix — iUstarmatrix

<dl>

 <dt>Weights</dt>
<dd>Weights that were trained by the ESOM algorithm</dd>

 <dt>Lines</dt>
<dd>Height of the used grid</dd>

 <dt>Columns</dt>
<dd>Width of the used grid</dd>

 <dt>Data</dt>
<dd>Matrix of Data that was used to train the ESOM. One datapoint per row</dd>

 <dt>Imx</dt>
<dd>Island mask that will be cut out from displayed Umatrix</dd>

 <dt>Cls</dt>
<dd>Classification of the Bestmatches</dd>

 <dt>Toroid</dt>
<dd>Are weights placed on a toroid grid?</dd>

</dl>

iUstarmatrix: iUstarmatrix

Description

Value

Arguments

References