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Towards Enhancement of Performance of K-Means Clustering Using Nature-Inspired Optimization Algorithms
Traditional K-means clustering algorithms have the drawback of getting stuck at local optima that depend on the random values of initial centroids. Optimization algorithms have their advantages in guiding iterative computation to search for global optima while avoiding local optima. The algorithms h...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Hindawi Publishing Corporation
2014
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4151373/ https://www.ncbi.nlm.nih.gov/pubmed/25202730 http://dx.doi.org/10.1155/2014/564829 |