Dynamic Clustering of Data with Modified K-Means Algorithm

@inproceedings{ShafeeqDynamicCO,
  title={Dynamic Clustering of Data with Modified K-Means Algorithm},
  author={Ahamed Shafeeq and ahamed. shafeeq}
}
  • Ahamed Shafeeq, ahamed. shafeeq
K-means is a widely used partitional clustering method. While there are considerable research efforts to characterize the key features of K-means clustering, further investigation is needed to reveal whether the optimal number of clusters can be found on the run based on the cluster quality measure. This paper presents a modified Kmeans algorithm with the intension of improving cluster quality and to fix the optimal number of cluster. The K-means algorithm takes number of clusters (K) as input… CONTINUE READING

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References

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SHOWING 1-10 OF 13 REFERENCES

Efficient Cluster Validation with K-Family Clusters on Quality Assessment

  • S. Prakash kumar, K. S. Ramaswami
  • European Journal of Scientific Research,
  • 2011
1 Excerpt

A M,Torkey F A, “An efficient enhanced k-means clustering algorithm

  • M FahimA, Salem
  • Journal of Zhejiang University Science ,
  • 2006

An efficient enhanced k - means clustering algorithm ”

  • M FahimA, M SalemA, A TorkeyF
  • Journal of Zhejiang University Science
  • 2006

II

  • R. Xu, D. Wunsch
  • “Survey of clustering algorithms”, IEEE Trans…
  • 2005

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