Fuzzy Sets & their Application to Clustering & Training

✍ Scribed by Beatrice Lazzerini (Author); Lakhmi C. Jain (Author); D. Dumitrescu (Author)

Publisher: CRC Press
Year: 2000
Leaves: 667
Edition: 1
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

Fuzzy set theory - and its underlying fuzzy logic - represents one of the most significant scientific and cultural paradigms to emerge in the last half-century. Its theoretical and technological promise is vast, and we are only beginning to experience its potential. Clustering is the first and most basic application of fuzzy set theory, but forms t

✦ Table of Contents

Fuzzy Sets. Entropy of Finite Fuzzy Partitions. Fuzziness and Non-Fuzziness Measures. Fuzzy Training Procedures. One-Level Classification: Cluster Substructure of a Fuzzy Class. One-Level Classification: Adaptive Algorithms. Cluster Validity. Convergence of Fuzzy clustering Algorithms. Fuzzy Discriminant Analysis and Related Clustering Criteria. Divisive Hierarchical Clustering. Classification with Structural Constraints. Classification in Pseudometric Spaces. Bibliography.

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✦ Subjects

Computer Science;Computer Engineering;Engineering & Technology;Electrical & Electronic Engineering;Electrical Engineering Communications;Intelligent Systems

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