Pattern Classification: Neuro-fuzzy Methods and Their Comparison / Edition 1

Pattern Classification: Neuro-fuzzy Methods and Their Comparison / Edition 1

by Shigeo Abe, S. Abe
     
 

ISBN-10: 1852333529

ISBN-13: 9781852333522

Pub. Date: 12/11/2000

Publisher: Springer London

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

Overview

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.

Product Details

ISBN-13:
9781852333522
Publisher:
Springer London
Publication date:
12/11/2000
Edition description:
2001
Pages:
327
Product dimensions:
6.10(w) x 9.25(h) x 0.24(d)

Table of Contents

Part I: Introduction. Multilayer Neural Network Classifiers. Support Vector Machines. Membership Functions. Static Fuzzy Rule Generation. Clustering. Tuning of Membership Functions. Robust Pattern Classification. Dynamic Fuzzy Rule Generation. Comparison of Classifier Performance. Optimizing Features. Generation of Training and Test Data Sets.-
Part II: Introduction. Fuzzy Rule Representation and Inference. Fuzzy Rule Generation. Robust Function Approximation.- Appendix A.- Appendix B.

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