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  • Article: Fuzzy Lattice Reasoning for Pattern Classification Using a New Positive Valuation Function
    Yazdan Jamshidi Khezeli, Hossein Nezamabadi-Pour
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    ABSTRACT: 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.
    Advances in Fuzzy Systems 04/2012; 8.

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