An empirical analysis on the stability of clustering algorithms

Reza Zafarani, Majid Makki, Ali A. Ghorbani

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

One of the aspects of a clustering algorithm that should be considered for choosing an appropriate algorithm in an unsupervised learning task is stability. A clustering algorithm is stable (on a dataset) if it results in the same clustering as it performed on the whole dataset, when actually performs on a (sub)sample of the dataset. In this paper, we report the results of an empirical study on the stability of two clustering algorithms, namely k-Means and normalized spectral clustering, along with some analysis on those results that are useful for practitioners who deal with scalability and researchers who employ stability as a tool for model selection.

Original languageEnglish (US)
Title of host publicationProceedings - 20th IEEE International Conference on Tools with Artificial Intelligence, ICTAI'08
Pages19-26
Number of pages8
DOIs
StatePublished - Dec 22 2008
Externally publishedYes
Event20th IEEE International Conference on Tools with Artificial Intelligence, ICTAI'08 - Dayton, OH, United States
Duration: Nov 3 2008Nov 5 2008

Publication series

NameProceedings - International Conference on Tools with Artificial Intelligence, ICTAI
Volume2
ISSN (Print)1082-3409

Other

Other20th IEEE International Conference on Tools with Artificial Intelligence, ICTAI'08
CountryUnited States
CityDayton, OH
Period11/3/0811/5/08

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence
  • Computer Science Applications

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  • Cite this

    Zafarani, R., Makki, M., & Ghorbani, A. A. (2008). An empirical analysis on the stability of clustering algorithms. In Proceedings - 20th IEEE International Conference on Tools with Artificial Intelligence, ICTAI'08 (pp. 19-26). [4669750] (Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI; Vol. 2). https://doi.org/10.1109/ICTAI.2008.62