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An Ontological and Epistemological Perspective of Fuzzy Set Theory by I. Burhan Türksen

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Chapter 5

FUZZY CLUSTERING METHOD

A particularly important concern in practice is to construct membership functions from a given set of data via unsupervised or supervised learning approaches. In general, membership functions may be constructed from available data when adequate amount of data is already collected in a database or a data warehouse. Naturally, the concern is extended beyond the acquisition or extraction of membership functions to the development of fuzzy system models, i.e., formation of fuzzy rule bases.

These are data-mining and knowledge discovery experiments with fuzzy clustering techniques. In these experiments, fuzzy clustering algorithms that extract and identify fuzzy clusters are the verifiers, i.e.,“truth” qualifiers. ...

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