Supervised Classification with Associative SOM
This paper presents an extension of the Self Organizing Map model called Associative SOM that is able to process different types of input data in separated data-paths. The ASOM model can easily deal with situations of incomplete data-patterns and incorporate class labels for supervisory purposes. The ASOM is successfully compared with Multilayer Perceptrons in the incremental classification of six erythemato-squamous diseases, where only partial data is available in successive steps.
KeywordsClass Label Hide Unit Radial Basis Function Winner Neuron Input Component
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