A hybrid monkey search algorithm for clustering analysis.
Clustering is a popular data analysis and data mining technique. The k-means clustering algorithm is one of the most commonly used methods. However, it highly depends on the initial solution and is easy to fall into local optimum solution. In view of the disadvantages of the k-means method, this pap...
| Published in: | Scientific World Journal pp. 938239 - 938240 |
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| Main Authors: | , , |
| Format: | research Journal Article |
| Published: |
Wiley-Blackwell
2014
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| Online Access: | View this record in EBSCOhost |
| Summary: | Clustering is a popular data analysis and data mining technique. The k-means clustering algorithm is one of the most commonly used methods. However, it highly depends on the initial solution and is easy to fall into local optimum solution. In view of the disadvantages of the k-means method, this paper proposed a hybrid monkey algorithm based on search operator of artificial bee colony algorithm for clustering analysis and experiment on synthetic and real life datasets to show that the algorithm has a good performance than that of the basic monkey algorithm for clustering analysis. |
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