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Investigation of an optimal number of clusters by the adaptive EM algorithm (CROSBI ID 666722)

Prilog sa skupa u zborniku | sažetak izlaganja sa skupa | međunarodna recenzija

Novoselac, Vedran Investigation of an optimal number of clusters by the adaptive EM algorithm // Book of Abstracts 17th International Conference on Operational Research KOI 2018 / Arnerić, Josip ; Čeh Časni, Anita (ur.). Zagreb: Printed by Fratres d.o.o., 2018. str. 22-22

Podaci o odgovornosti

Novoselac, Vedran

engleski

Investigation of an optimal number of clusters by the adaptive EM algorithm

This paper considers the investigation of an optimal number of clusters for datasets that are modeled as the Gaussian mixture. For that purpose, an adaptive method that is based on the modified Expectation Maximization (EM) algorithm is developed. The modification is conducted within the hidden variable of the standard EM algorithm. Assuming that data are multivariate normally distributed where each component of Gaussian mixture corresponds to one cluster, the modification is provided by utilizing the fact that the Mahalanobis distance of samples follows a Chi-square distribution. Besides, the quantity measure is constructed in order to determine number of clusters. The proposed method is presented in several numerical examples.

Clustering ; EM ; Gaussian mixture ; Mahalanobis distance ; Chi-square

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Podaci o prilogu

22-22.

2018.

objavljeno

Podaci o matičnoj publikaciji

Book of Abstracts 17th International Conference on Operational Research KOI 2018

Arnerić, Josip ; Čeh Časni, Anita

Zagreb: Printed by Fratres d.o.o.

1849-5141

Podaci o skupu

17th International Conference on Operational Research (KOI 2018)

predavanje

26.09.2018-28.09.2018

Zadar, Hrvatska

Povezanost rada

Matematika, Računarstvo