SIMULATION OF ENHANCED KMEAN CLUSTERING MECHENISM ON MATLAB Nancy, nancymalik339@

Authors

  • Nancy

Keywords:

Clustering, K-Mean, Data Mining

Abstract

K-means clustering is very Fast, robust & easily understandable. If data set is separated from one other data set, then it gives best results. Clusters do not having overlapping character & are also non-hierarchical within nature. Some challenges are related to visualization & querying of data. Scientist has faced several challenges in e-Science such as meteorology, complicated physics simulation & environmental researches. Lot of challenges has been faced due to big data in case of biology & genomics. Problems with existing system were search, sharing, storage, transfer, and visualization, querying-updating. These problems can be reduced by using proposed algorithm. In this paper we have explain clustering & proposed algorithm is discussed. We have simulated the enhanced K-Mean clustering using MATLAB.

References

Hong Liu 1,&Xiaohong Yu (2009), “Application Research of Clustering Algorithm in Image Retrieval System”.International Journal of Database Theory & Application.

Dr. Yashpal singh, 2alok singh chauhan in (2009), “neural networks in data mining” International Journal of Research, Mar (2009).

Jiawei Han & Jing on (2011) “Research Challenges for Data Mining in Science & Engineering” International Journal of Scientific&Research Publications ,March (2011).

Navjot Kaur, Jaspreet Kaur Sahiwal, Navneet Kaur (2012), “Efficient Clustering Algorithm Using Ranking Method In Data Mining” ” International Arab Journal of Information Technology, July (2012).

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Published

2018-03-30

How to Cite

Nancy. (2018). SIMULATION OF ENHANCED KMEAN CLUSTERING MECHENISM ON MATLAB Nancy, nancymalik339@. Innovative Research Thoughts, 4(1), 64–69. Retrieved from https://irt.shodhsagar.com/index.php/j/article/view/427