The week's pick
Reseach Article
An Improved Clustering Approach on Time Series Data Set
| National Workshop-Cum-Conference on Recent Trends in Mathematics and Computing 2011 |
| Foundation of Computer Science USA |
| RTMC - Number 4 |
| May 2012 |
| Authors: Pallavi, Sunila Godara |
| aab508c0-f34d-4622-92cf-4f499e387def |
Pallavi, Sunila Godara . An Improved Clustering Approach on Time Series Data Set. National Workshop-Cum-Conference on Recent Trends in Mathematics and Computing 2011. RTMC, 4 (May 2012), 16-20.
Abstract
In clustering, objects are clustered or grouped based on the principle of maximizing the intra-class similarity and minimizing the inter-class similarity. This paper proposes use of BIRCH hierarchical clustering method on large amount of numerical data by integration of hierarchical clustering and other clustering methods such as iterative partitioning methods such as k-means and k-medoids and their comparison. Clustering feature and clustering feature tree (CF tree) will be used to summarize cluster representations. With this clustering method we can achieve good speed and scalability.
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