Multivariate Beta Mixture Model: Probabilistic Clustering with Flexible Cluster Shapes

Yung Peng Hsu; Hung Hsuan Chen

doi:10.1007/978-981-97-2242-6_19

Multivariate Beta Mixture Model: Probabilistic Clustering with Flexible Cluster Shapes

Yung Peng Hsu, Hung Hsuan Chen

Department of Computer Science and Information Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

This paper introduces the multivariate beta mixture model (MBMM), a new probabilistic model for soft clustering. MBMM adapts to diverse cluster shapes because of the flexible probability density function of the multivariate beta distribution. We introduce the properties of MBMM, describe the parameter learning procedure, and present the experimental results, showing that MBMM fits diverse cluster shapes on synthetic and real datasets. The code is released anonymously at https://github.com/hhchen1105/mbmm/.

Original language	English
Title of host publication	Advances in Knowledge Discovery and Data Mining - 28th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2024, Proceedings
Editors	De-Nian Yang, Xing Xie, Vincent S. Tseng, Jian Pei, Jen-Wei Huang, Jerry Chun-Wei Lin
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	233-245
Number of pages	13
ISBN (Print)	9789819722419
DOIs	https://doi.org/10.1007/978-981-97-2242-6_19
State	Published - 2024
Event	28th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2024 - Taipei, Taiwan Duration: 7 May 2024 → 10 May 2024

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	14645 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	28th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2024
Country/Territory	Taiwan
City	Taipei
Period	7/05/24 → 10/05/24

Keywords

Clustering
EM algorithm
Mixture model

Access to Document

10.1007/978-981-97-2242-6_19

Cite this

Hsu, Y. P., & Chen, H. H. (2024). Multivariate Beta Mixture Model: Probabilistic Clustering with Flexible Cluster Shapes. In D.-N. Yang, X. Xie, V. S. Tseng, J. Pei, J.-W. Huang, & J. C.-W. Lin (Eds.), Advances in Knowledge Discovery and Data Mining - 28th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2024, Proceedings (pp. 233-245). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 14645 LNAI). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-981-97-2242-6_19

Hsu, Yung Peng ; Chen, Hung Hsuan. / Multivariate Beta Mixture Model : Probabilistic Clustering with Flexible Cluster Shapes. Advances in Knowledge Discovery and Data Mining - 28th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2024, Proceedings. editor / De-Nian Yang ; Xing Xie ; Vincent S. Tseng ; Jian Pei ; Jen-Wei Huang ; Jerry Chun-Wei Lin. Springer Science and Business Media Deutschland GmbH, 2024. pp. 233-245 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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Hsu, YP & Chen, HH 2024, Multivariate Beta Mixture Model: Probabilistic Clustering with Flexible Cluster Shapes. in D-N Yang, X Xie, VS Tseng, J Pei, J-W Huang & JC-W Lin (eds), Advances in Knowledge Discovery and Data Mining - 28th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2024, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 14645 LNAI, Springer Science and Business Media Deutschland GmbH, pp. 233-245, 28th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2024, Taipei, Taiwan, 7/05/24. https://doi.org/10.1007/978-981-97-2242-6_19

Multivariate Beta Mixture Model: Probabilistic Clustering with Flexible Cluster Shapes. / Hsu, Yung Peng; Chen, Hung Hsuan.
Advances in Knowledge Discovery and Data Mining - 28th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2024, Proceedings. ed. / De-Nian Yang; Xing Xie; Vincent S. Tseng; Jian Pei; Jen-Wei Huang; Jerry Chun-Wei Lin. Springer Science and Business Media Deutschland GmbH, 2024. p. 233-245 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 14645 LNAI).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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Hsu YP, Chen HH. Multivariate Beta Mixture Model: Probabilistic Clustering with Flexible Cluster Shapes. In Yang DN, Xie X, Tseng VS, Pei J, Huang JW, Lin JCW, editors, Advances in Knowledge Discovery and Data Mining - 28th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2024, Proceedings. Springer Science and Business Media Deutschland GmbH. 2024. p. 233-245. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-981-97-2242-6_19