Fuzzy Lattice Reasoning for Pattern Classification Using a New Positive Valuation Function
Keyword(s):
This paper describes an enhancement of fuzzy lattice reasoning (FLR) classifier for pattern classification based on a positive valuation function. Fuzzy lattice reasoning (FLR) was described lately as a lattice data domain extension of fuzzy ARTMAP neural classifier based on a lattice inclusion measure function. In this work, we improve the performance of FLR classifier by defining a new nonlinear positive valuation function. As a consequence, the modified algorithm achieves better classification results. The effectiveness of the modified FLR is demonstrated by examples on several well-known pattern recognition benchmarks.
2009 ◽
Vol 72
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pp. 2067-2078
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2004 ◽
Vol 14
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pp. 104-113
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1996 ◽
Vol 8
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pp. 403-428
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2011 ◽
Vol 22
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pp. 57-68
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