Fuzzy clustering with partial supervision

Fuzzy clustering with partial supervision

Presented here is a problem of fuzzy clustering with partial supervision, i.e., unsupervised learning completed in the presence of some labeled patterns. The classification information is incorporated additively as a part of an objective function utilized in the standard FUZZY ISODATA. The algorithm...

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Veröffentlicht in:IEEE transactions on systems, man and cybernetics. Part B, Cybernetics man and cybernetics. Part B, Cybernetics, 1997-10, Vol.27 (5), p.787-795
Hauptverfasser: Pedrycz, W., Waletzky, J.
Format: Artikel
Sprache:eng
Schlagworte:
Clustering algorithms
Clustering methods
Euclidean distance
Fuzzy sets
Organizing
Prototypes
Shape
Software engineering
Software reusability
Unsupervised learning
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Zusammenfassung:Presented here is a problem of fuzzy clustering with partial supervision, i.e., unsupervised learning completed in the presence of some labeled patterns. The classification information is incorporated additively as a part of an objective function utilized in the standard FUZZY ISODATA. The algorithms proposed in the paper embrace two specific learning scenarios of complete and incomplete class assignment of the labeled patterns. Numerical examples including both synthetic and real-world data arising in the realm of software engineering are also provided.
ISSN:1083-4419
1941-0492
DOI:10.1109/3477.623232