Unique distance measure approach for K-means (UDMA-Km) clustering algorithm

@article{Pun2007UniqueDM,
  title={Unique distance measure approach for K-means (UDMA-Km) clustering algorithm},
  author={W.K.D. Pun and A. S. Ali},
  journal={TENCON 2007 - 2007 IEEE Region 10 Conference},
  year={2007},
  pages={1-4}
}
Clustering technique in data mining has received a significant amount of attention from machine learning community in the last few years and become one of the fundamental research areas. Among the vast range of clustering algorithms, K-means is one of the most popular clustering algorithms. The basic principle of the K-means algorithm is to know how different distance measure is defined. It is a critical issue for K-means users. For example, how can we select a unique distance measure method… CONTINUE READING

References

Publications referenced by this paper.
Showing 1-10 of 16 references

A tutorial on clustering algorithms,

  • M. Matteucci
  • http://www. elet.polimi.it/upload/matteucc…
  • 2007
Highly Influential
4 Excerpts

Clustering,” http://www.cs.bris.ac.uk/home/tr1690/ documentation/fuzzy clustering initial report/node11.html

  • T. Rashid
  • accessed on 27th April,
  • 2007
1 Excerpt

K-Means clustering,

  • B. T. Luke
  • http://fconyx.ncifcrf.gov/∼lukeb/ kmeans.html…
  • 2007
1 Excerpt

Zalane, “Principles of knowledge discovery in databases

  • O R.
  • http://www.cs.ualberta.ca/%Ezaiane/courses…
  • 2007
2 Excerpts

K-means and hierarchical clustering - tutorial slides,

  • A. Moore
  • http://www-2.cs.cmu.edu/∼awm/tutorials/keans.html…
  • 2004
1 Excerpt

Nonhierarchical clustering Some methods for classification and analysis of multivariate observations

  • J. F. Horrell
  • Data Mining Introductory and Advanced Topics
  • 2003

Mathematical Statistics

  • J. Shao
  • New York: Springer-Verlag
  • 1999
1 Excerpt

Similar Papers

Loading similar papers…