An extension of partially supervised fuzzy cluster analysis

We propose an approach to handling class information in fuzzy cluster analysis, where a class can consist of several clusters. The approach is based on a penalty term for clusters comprising several clusters.

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Bibliographic Details
Main Authors: Timm, H., Klawonn, F., Kruse, R.
Format: Conference Proceeding
Language:English
Subjects:
Clustering algorithms
Computer science
Equations
Fuzzy sets
Information analysis
Prototypes
Shape
Zinc
Online Access:Request full text
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Description
Summary:We propose an approach to handling class information in fuzzy cluster analysis, where a class can consist of several clusters. The approach is based on a penalty term for clusters comprising several clusters.
DOI:10.1109/NAFIPS.2002.1018031