Babu, Phanendra G and Murty, Narasimha M (1993) A near-optimal initial seed value selection in K-means means algorithm using a genetic algorithm. In: Pattern Recognition Letters, 14 (10). pp. 763-769.Full text not available from this repository.
The K-means algorithm for clustering is very much dependent on the initial seed values. We use a genetic algorithm to find a near-optimal partitioning of the given data set by selecting proper initial seed values in the K-means algorithm. Results obtained are very encouraging and in most of the cases, on data sets having well separated clusters, the proposed scheme reached a global minimum.
|Item Type:||Journal Article|
|Additional Information:||Copyright of this article belongs to Elsevier Science.|
|Keywords:||Clustering;seed values;optimal partition;genetic algorithms; K-means algorithm.|
|Department/Centre:||Division of Electrical Sciences > Computer Science & Automation (Formerly, School of Automation)|
|Date Deposited:||31 Jan 2011 11:50|
|Last Modified:||31 Jan 2011 11:50|
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