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Contradiction resolution with explicit and limited evaluation and its application to SOM.

Authors :
Kamimura, Ryotaro
Source :
2013 International Joint Conference on Neural Networks (IJCNN); 2013, p1-8, 8p
Publication Year :
2013

Abstract

In this paper, we improve contradiction resolution method. In contradiction resolution, a neuron is self-evaluated to fire without considering other neurons. On the other hand, a neuron is outer-evaluated by considering all neighboring neurons. We improve contradiction resolution by separating the results by self-evaluation from those by outer-evaluation and by limiting the number of winning neurons. The explicit separation is used to enhance contradiction between self and outer-evaluation. The reduction of the number of winning neurons is to focus on a limited number of neurons for extracting main characteristics of input patterns. We applied contradiction resolution to the Senate data. Experimental results confirmed that improved prediction was accompanied by improved visualization and interpretation performance. [ABSTRACT FROM PUBLISHER]

Details

Language :
English
ISBNs :
9781467361293
Database :
Complementary Index
Journal :
2013 International Joint Conference on Neural Networks (IJCNN)
Publication Type :
Conference
Accession number :
94558274
Full Text :
https://doi.org/10.1109/IJCNN.2013.6706999