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Reducing the Time Requirement of k-Means Algorithm
Traditional k-means and most k-means variants are still computationally expensive for large datasets, such as microarray data, which have large datasets with large dimension size d. In k-means clustering, we are given a set of n data points in d-dimensional space R(d) and an integer k. The problem i...
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| Main Authors: | , , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Public Library of Science
2012
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC3519838/ https://ncbi.nlm.nih.gov/pubmed/23239974 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0049946 |
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