A branch-and-cut SDP-based algorithm for minimum sum-of-squares clustering
Minimum sum-of-squares clustering (MSSC) consists in partitioning a given set of n points into k clusters in order to minimize the sum of squared distances from the points to the centroid of their cluster. Recently, Peng & Xia (2005) established the equivalence between 0-1 semidefinite progr...
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| Formato: | article |
| Idioma: | eng |
| Publicado em: |
2009
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| Texto completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-74382009000300002 |
| País: | Brasil |
| Oai: | oai:scielo:S0101-74382009000300002 |