A hybridized approach to data clustering

  title={A hybridized approach to data clustering},
  author={Yi-Tung Kao and Erwie Zahara and I-Wei Kao},
  journal={Expert Syst. Appl.},
Data clustering helps one discern the structure of and simplify the complexity of massive quantities of data. It is a common technique for statistical data analysis and is used in many fields, including machine learning, data mining, pattern recognition, image analysis, and bioinformatics, in which the distribution of information can be of any size and shape. The well-known K-means algorithm, which has been successfully applied to many practical clustering problems, suffers from several… CONTINUE READING
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Publications referenced by this paper.
Showing 1-10 of 17 references

Particle swarm optimization

  • J. Kennedy, R. C. Eberhart
  • Proceedings of the IEEE International Joint…
  • 1995
Highly Influential
3 Excerpts

Hybrid simplex search and particle swarm optimization for the global optimization of multimodal functions

  • Fan, S S-K., Liang, Y-C, E Zahara
  • Engineering Optimization,
  • 2004
1 Excerpt

Particle swarm optimization algorithm and its application to clustering analysis

  • Chen, C-Y, F. Ye
  • Proceedings of the 2004 IEEE International…
  • 2004

Tracking and optimizing dynamic systems with particle swarms

  • R. C. Eberhart, Y. Shi
  • Proceedings of the Congress on Evolutionary…
  • 2001
1 Excerpt

Tracking dynamic systems with PSO: where’s the cheese?

  • X. Hu, R. C. Eberhart
  • 2001
1 Excerpt

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