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Pregled bibliografske jedinice broj: 1011322

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


Novoselac, Vedran
Investigation of the optimal number of clusters by the adaptive EM algorithm // Croatian operational research review, 10 (2019), 1; 1-12 doi:10.17535/crorr.2019.0001 (međunarodna recenzija, članak, znanstveni)


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

Autori
Novoselac, Vedran

Izvornik
Croatian operational research review (1848-0225) 10 (2019), 1; 1-12

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

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

Sažetak
This paper considers the investigation of the optimal number of clusters for datasets that are modeled as the Gaussian mixture. For that purpose, the adaptive method that is based on a modi ed Expectation Maximization (EM) algorithm is developed. The modi cation is conducted within the hidden variable of the standard EM algorithm. Assuming that data are multivariate normally distributed, where each component of the Gaussian mixture corresponds to one cluster, the modi ca- tion 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.

Izvorni jezik
Engleski

Znanstvena područja
Matematika, Računarstvo



POVEZANOST RADA


Ustanove:
Strojarski fakultet, Slavonski Brod,
Sveučilište J. J. Strossmayera u Osijeku

Profili:

Avatar Url Vedran Novoselac (autor)

Poveznice na cjeloviti tekst rada:

doi hrcak.srce.hr hrcak.srce.hr

Citiraj ovu publikaciju:

Novoselac, Vedran
Investigation of the optimal number of clusters by the adaptive EM algorithm // Croatian operational research review, 10 (2019), 1; 1-12 doi:10.17535/crorr.2019.0001 (međunarodna recenzija, članak, znanstveni)
Novoselac, V. (2019) Investigation of the optimal number of clusters by the adaptive EM algorithm. Croatian operational research review, 10 (1), 1-12 doi:10.17535/crorr.2019.0001.
@article{article, author = {Novoselac, Vedran}, year = {2019}, pages = {1-12}, DOI = {10.17535/crorr.2019.0001}, keywords = {Clustering, EM, Gaussian mixture, Mahalanobis distance, Chi-square}, journal = {Croatian operational research review}, doi = {10.17535/crorr.2019.0001}, volume = {10}, number = {1}, issn = {1848-0225}, title = {Investigation of the optimal number of clusters by the adaptive EM algorithm}, keyword = {Clustering, EM, Gaussian mixture, Mahalanobis distance, Chi-square} }
@article{article, author = {Novoselac, Vedran}, year = {2019}, pages = {1-12}, DOI = {10.17535/crorr.2019.0001}, keywords = {Clustering, EM, Gaussian mixture, Mahalanobis distance, Chi-square}, journal = {Croatian operational research review}, doi = {10.17535/crorr.2019.0001}, volume = {10}, number = {1}, issn = {1848-0225}, title = {Investigation of the optimal number of clusters by the adaptive EM algorithm}, keyword = {Clustering, EM, Gaussian mixture, Mahalanobis distance, Chi-square} }

Časopis indeksira:


  • Web of Science Core Collection (WoSCC)
    • Emerging Sources Citation Index (ESCI)
  • Scopus
  • EconLit


Uključenost u ostale bibliografske baze podataka::


  • EconLit
  • INSPEC
  • MathSciNet
  • Zentrallblatt für Mathematik/Mathematical Abstracts


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