An Extended K-Means Clustering with Genetic Algorithm and Min-Max Approach |
Author(s): |
| Vibhuti P. Patel , GIDC DEGREE ENGINEERING COLLEGE- NAVSARI; Avani P. Patel, GIDC DEGREE ENGINEERING COLLEGE- NAVSARI; Mihir A. Mishra, GIDC DEGREE ENGINEERING COLLEGE- NAVSARI; Kushal D. Patel, GIDC DEGREE ENGINEERING COLLEGE- NAVSARI; Pragnesh A. Patel, GIDC DEGREE ENGINEERING COLLEGE- NAVSARi |
Keywords: |
| Min-Max Approach, Genetic Algorithm |
Abstract |
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Clustering is one of the major data mining task that is division of data object into similar group; each similar group is called cluster. Object in the cluster are similar to each other and dissimilar with different cluster. It can be implemented by number of approaches. K means is one of the popular techniques for the clustering. Major drawbacks of the K means clustering algorithm are cluster depends on initial centroid and predefined value of k (cluster number). From the previous research work it has been found that GA (Genetic Algorithm) can be used to solve clustering problem and Min-Max approach can be used to improve robustness. This work proposes an extended clustering algorithm that combines the GA and K-means with Min-Max approach. |
Other Details |
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Paper ID: IJSRDV4I40727 Published in: Volume : 4, Issue : 4 Publication Date: 01/07/2016 Page(s): 844-846 |
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