DocumentCode :
445850
Title :
A vigilance-free ART network with general geometry internal categories
Author :
Gomes, D. ; Fernández-Delgado, M. ; Barro, Senen
Author_Institution :
Dept. of Electron. & Comput. Sci., Santiago de Compostela Univ., Spain
Volume :
1
fYear :
2005
fDate :
31 July-4 Aug. 2005
Firstpage :
463
Abstract :
ART neural networks are important tools for online supervised pattern recognition. They use internal categories with pre-defined geometry, given by the category choice function. Pre-defined geometry limits the ability of the categories to fit complex borders among output predictions for a given data set, and may contribute to the category proliferation problem. This work proposes Polytope ARTMAP (PTAM), whose category representation regions have general geometry-polytopes in Rn whose vertices are selected training patterns. The category borders compose a piece-wise linear approximation to the borders among predictions. Overlapping among categories is avoided in PTAM because they do not need to overlap in order to keep their geometry during learning. The choice function does not depend on the category size. Category growing is only limited by the other categories, and the vigilance parameter can be removed, so that PTAM learns a training data set without any parameter tuning.
Keywords :
ART neural nets; geometry; learning (artificial intelligence); ART neural network; category choice function; category proliferation problem; category representation; general geometry internal category; geometry-polytopes; online supervised pattern recognition; piecewise linear approximation; polytope ARTMAP; vigilance-free ART network; Computational geometry; Computer science; Electronic mail; Humans; Management training; Neural networks; Pattern recognition; Piecewise linear techniques; Subspace constraints; Training data;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 2005. IJCNN '05. Proceedings. 2005 IEEE International Joint Conference on
Print_ISBN :
0-7803-9048-2
Type :
conf
DOI :
10.1109/IJCNN.2005.1555875
Filename :
1555875
Link To Document :
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