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. © Springer-Verlag Berlin Heidelberg 2003.
CITATION STYLE
Del-Hoyo, R., Buldain, D., & Marco, A. (2003). Supervised classification with associative SOM. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2686, 334–341. https://doi.org/10.1007/3-540-44868-3_43
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