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EPIA
2005
Springer

An Extension of Self-organizing Maps to Categorical Data

10 years 5 months ago
An Extension of Self-organizing Maps to Categorical Data
Self-organizing maps (SOM) have been recognized as a powerful tool in data exploratoration, especially for the tasks of clustering on high dimensional data. However, clustering on categorical data is still a challenge for SOM. This paper aims to extend standard SOM to handle feature values of categorical type. A batch SOM algorithm (NCSOM) is presented concerning the dissimilarity measure and update method of map evolution for both numeric and categorical features simultaneously.
Ning Chen, Nuno C. Marques
Added 27 Jun 2010
Updated 27 Jun 2010
Type Conference
Year 2005
Where EPIA
Authors Ning Chen, Nuno C. Marques
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