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Pattern Classification

Neuro-fuzzy Methods and Their Comparison
Springer Book Archives
1st Edition. 2000. Buch. xix, 327 S.: Bibliographien. Hardcover
Springer ISBN 978-1-85233-352-2
Format (B x L): 15,5 x 23,5 cm
Gewicht: 1480 g
In englischer Sprache
This book provides a unified approach for developing a fuzzy classifier and explains the advantages and disadvantages of different classifiers through extensive performance evaluation of real data sets. It thus offers new learning paradigms for analyzing neural networks and fuzzy systems, while training fuzzy classifiers. Function approximation is also treated and function approximators are compared.

Audience

Professional/practitioner

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The unified approach for extracting fuzzy rules against different fuzzy classifier architectures A new learning paradigm for neural network classifiers based on the network synthesis principle Extensive performance comparisons including conventional classifiers