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Titolo:
Reinterpreting the category utility function
Autore:
Mirkin, B;
Indirizzi:
Univ London Birkbeck Coll, Sch Comp Sci & Informat Syst, London WC1E 7HX, England Univ London Birkbeck Coll London England WC1E 7HX ndon WC1E 7HX, England Rutgers State Univ, Ctr Discrete Math & Theoret Comp Sci, Piscataway, NJ 08854 USA Rutgers State Univ Piscataway NJ USA 08854 Sci, Piscataway, NJ 08854 USA
Titolo Testata:
MACHINE LEARNING
fascicolo: 2, volume: 45, anno: 2001,
pagine: 219 - 228
SICI:
0885-6125(2001)45:2<219:RTCUF>2.0.ZU;2-7
Fonte:
ISI
Lingua:
ENG
Keywords:
clustering; data standardization; contingency coefficient; correlation ratio; weighting features; mixed-scale data;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Engineering, Computing & Technology
Citazioni:
9
Recensione:
Indirizzi per estratti:
Indirizzo: Mirkin, B Univ London Birkbeck Coll, Sch Comp Sci & Informat Syst, Malet St, London WC1E 7HX, England Univ London Birkbeck Coll Malet St London England WC1E 7HX land
Citazione:
B. Mirkin, "Reinterpreting the category utility function", MACH LEARN, 45(2), 2001, pp. 219-228

Abstract

The category utility function is a partition quality scoring function applied in some clustering programs of machine learning. We reinterpret this function in terms of the data variance explained by a clustering, or, equivalently, in terms of the square-error classical clustering criterion that administers the K-Means and Ward methods. This analysis suggests extensions ofthe scoring function to situations with differently standardized and mixedscale data.

ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 04/06/20 alle ore 08:05:21