Hybrid minimal spanning tree and mixture of Gaussians based clustering algorithm

Agnes Vathy-Fogarassy, Attila Kiss, Janos Abonyi

Research output: Conference contribution

13 Citations (Scopus)

Abstract

Clustering is an important tool to explore the hidden structure of large databases. There are several algorithms based on different approaches (hierarchical, partitional, density-based, model-based, etc.). Most of these algorithms have some discrepancies, e.g. they are not able to detect clusters with convex shapes, the number of the clusters should be a priori known, they suffer from numerical problems, like sensitiveness to the initialization, etc. In this paper we introduce a new clustering algorithm based on the sinergistic combination of the hierarchial and graph theoretic minimal spanning tree based clustering and the partitional Gaussian mixture model-based clustering algorithms. The aim of this hybridization is to increase the robustness and consistency of the clustering results and to decrease the number of the heuristically defined parameters of these algorithms to decrease the influence of the user on the clustering results. As the examples used for the illustration of the operation of the new algorithm will show, the proposed algorithm can detect clusters from data with arbitrary shape and does not suffer from the numerical problems of the Gaussian mixture based clustering algorithms.

Original languageEnglish
Title of host publicationFoundations of Information and Knowledge Systems - 4th International Symposium, FoIKS 2006, Proceedings
Pages313-330
Number of pages18
DOIs
Publication statusPublished - júl. 6 2006
Event4th International Symposium on Foundations of Information and Knowledge Systems, FoIKS 2006 - Budapest, Hungary
Duration: febr. 14 2006febr. 17 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3861 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other4th International Symposium on Foundations of Information and Knowledge Systems, FoIKS 2006
CountryHungary
CityBudapest
Period2/14/062/17/06

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Vathy-Fogarassy, A., Kiss, A., & Abonyi, J. (2006). Hybrid minimal spanning tree and mixture of Gaussians based clustering algorithm. In Foundations of Information and Knowledge Systems - 4th International Symposium, FoIKS 2006, Proceedings (pp. 313-330). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3861 LNCS). https://doi.org/10.1007/11663881_18