The week's pick
Reseach Article
An Alternative Technique of Selecting the Initial Cluster Centers in the k-means Algorithm for Better Clustering
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 67 - Number 7 |
| Year of Publication: 2013 |
| Authors: Sisir Kumar Rajbongshi, Anjana Kakoti Mahanta |
10.5120/11409-6736
|
Sisir Kumar Rajbongshi, Anjana Kakoti Mahanta . An Alternative Technique of Selecting the Initial Cluster Centers in the k-means Algorithm for Better Clustering. International Journal of Computer Applications. 67, 7 ( April 2013), 28-31. DOI=10.5120/11409-6736
Abstract
Although k-means works well in many cases it offers no accuracy guarantee and it has no idea to select ideal cluster representatives. This article presents a technique in which the initial cluster representatives in the standard k-means algorithm are chosen intelligently. Comparison of the quality of the clusters produced by the standard k-means algorithm, k-means using Furthest-First, and k-means using the proposed initialization technique have investigated. Experiment result shows that the quality of the clusters improves with the proposed algorithm in most of the cases.
References
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- Shuttle Dataset Available: http://mlr. cs. umass. edu/ml/datasets/stalog+(shuttle)
- Synthetic Control Chart Time Series Dataset Available: http://archive. ics. uci. edu/ml/datasets/synthetic+control+chart+time+series
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