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Fuzzy Sets & their Application to Clustering & Training (International Series on Computational Intelligence)
 
 
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Fuzzy Sets & their Application to Clustering & Training (International Series on Computational Intelligence) [Hardcover]

Beatrice Lazzerini (Author), Lakhmi C. Jain (Author), D. Dumitrescu (Author)

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Book Description

0849305896 978-0849305894 March 24, 2000 1
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 the basis of many, more sophisticated, intelligent computational models, particularly in pattern recognition, data mining, adaptive and hierarchical clustering, and classifier design.

Fuzzy Sets and their Application to Clustering and Training offers a comprehensive introduction to fuzzy set theory, focusing on the concepts and results needed for training and clustering applications. It provides a unified mathematical framework for fuzzy classification and clustering, a methodology for developing training and classification methods, and a general method for obtaining a variety of fuzzy clustering algorithms.
The authors - top experts from around the world - combine their talents to lay a solid foundation for applications of this powerful tool, from the basic concepts and mathematics through the study of various algorithms, to validity functionals and hierarchical clustering. The result is Fuzzy Sets and their Application to Clustering and Training - an outstanding initiation into the world of fuzzy learning classifiers and fuzzy clustering.

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Inside This Book (learn more)
First Sentence:
Fuzzy sets represent a suitable mathematical tool for the modeling of imprecision and vagueness. Read the first page
Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
binary fuzzy partition, new fuzzy partition, fuzzy discriminant analysis, fuzzy perceptron, fuzzy relaxation procedure, cluster validity functionals, shell clustering algorithms, disjoint fuzzy sets, fuzzy measure space, weighted inertia, cluster substructure, fuzzy hierarchy, optimal cluster number, optimal membership degrees, optimal prototypes, proportion exponent, hierarchical pattern recognition, fuzzy class, informational energy, sharpness relation, classification entropy, optimal fuzzy partition, shell algorithm, pocket algorithm, fuzzy partitions
Key Phrases - Capitalized Phrases (CAPs): (learn more)
New York, Definition Let, Proposition Let, Studia Univ, Plenum Press, Prentice Hall, Englewood Cliffs, Operational Research, Fuzzy Objective Function Algorithms, Maximum Likelihood Estimation, Babeq-Bolyai Ser, Romanian Academy Publishing House, Academic Press, Babe-Bolyai Ser, Babes-Bolyai Ser, Mathematical Principles of Classification Theory, North Holland, Studio Univ, Approximate Reasoning, Cornell University, Decision Analysis, Fuzzy Mathematics, General Systems, Remark Let, Springer Verlag
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