On the application of bio-inspired optimization algorithms to fuzzy C-Means clustering of time series

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

Abstract

Fuzzy c-means clustering (FCM) is a clustering method which is based on the partial membership concept. As with the other clustering methods, FCM applies a distance to cluster the data. While the Euclidean distance is widely-used to perform the clustering task, other distances have been suggested in the literature. In this paper we study the use of a weighted combination of metrics in FCM clustering of time series where the weights in the combination are the outcome of an optimization process using differential evolution, genetic algorithms, and particle swarm optimization as optimizers. We show how the overfitting phenomenon interferes in the optimization process that the optimal results obtained during the training stage degrade during the testing stage as a result of overfitting.

Original languageEnglish
Title of host publicationICPRAM 2015 - Proceedings of the International Conference on Pattern Recognition Applications and Methods, Volume 1, Lisbon, Portugal, 10-12 January, 2015
EditorsMaria De Marsico, Mario Figueiredo, Ana Fred
PublisherSciTePress
Pages348-353
Number of pages6
Volume1
ISBN (Electronic)9789897580765
Publication statusPublished - 2015
Externally publishedYes
Event4th International Conference on Pattern Recognition Applications and Methods - Lisbon, Portugal
Duration: 10 Jan 201512 Jan 2015
Conference number: 4th

Publication series

NameICPRAM 2015 - 4th International Conference on Pattern Recognition Applications and Methods, Proceedings
Volume1

Conference

Conference4th International Conference on Pattern Recognition Applications and Methods
Abbreviated title ICPRAM 2015
CountryPortugal
CityLisbon
Period10/01/1512/01/15

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Keywords

  • Data mining
  • Differential evolution
  • Distance metrics
  • Fuzzy C-Means clustering
  • Genetic algorithms
  • Overfitting
  • Particle swarm optimization
  • Time series

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

Cite this

Fuad, M. M. M. (2015). On the application of bio-inspired optimization algorithms to fuzzy C-Means clustering of time series. In M. De Marsico, M. Figueiredo, & A. Fred (Eds.), ICPRAM 2015 - Proceedings of the International Conference on Pattern Recognition Applications and Methods, Volume 1, Lisbon, Portugal, 10-12 January, 2015 (Vol. 1, pp. 348-353). (ICPRAM 2015 - 4th International Conference on Pattern Recognition Applications and Methods, Proceedings; Vol. 1). SciTePress.