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Titolo:
AN OPTIMIZATION FOR CLASSIFICATION MAXIMUM-LIKELIHOOD CRITERION
Autore:
WON CS;
Indirizzi:
DONGGUK UNIV,DEPT ELECTR ENGN,PIL DONG,CHUNG GU SEOUL 100715 SOUTH KOREA GOLDSTAR,CONSUMER PROD LAB E1 SEOUL SOUTH KOREA
Titolo Testata:
Pattern recognition letters
fascicolo: 5, volume: 14, anno: 1993,
pagine: 363 - 367
SICI:
0167-8655(1993)14:5<363:AOFCMC>2.0.ZU;2-8
Fonte:
ISI
Lingua:
ENG
Keywords:
CLUSTERING; CLASSIFICATION MAXIMUM LIKELIHOOD CRITERION; K-MEANS; MOVING METHOD;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
CompuMath Citation Index
Science Citation Index Expanded
Citazioni:
7
Recensione:
Indirizzi per estratti:
Citazione:
C.S. Won, "AN OPTIMIZATION FOR CLASSIFICATION MAXIMUM-LIKELIHOOD CRITERION", Pattern recognition letters, 14(5), 1993, pp. 363-367

Abstract

A clustering criterion introduced by Symons (1981), which is called Classification Maximum Likelihood (CML) criterion in this paper, is designed to consider the cluster size and the covariance structure of samples. The CML criterion is optimized by the 'Moving method' suggested by Duda and Hart (1973, p. 226). When the Moving method is applied to the CML criterion with an arbitrary initial cluster, it often yields degenerate clusters. To avoid such degenerate cases, we propose two stages of clustering. In the first stage, we roughly partition samples with respect to 'the covariance structure component' in the CML criterion. The resulting partition is then further clustered with the full CMLcriterion.

ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 02/10/20 alle ore 01:49:13