The core of a k-means algorithm is the reallocation phase. A varietyof schemes have been suggested for moving entities from one cluster to another and each of them maygive a di(erent clustering even though the data set is the same. The present paper describes shortcomings and relative merits of 17 relocation methods in connection with randomlygenerated data sets.
A computational study of several relocation methods for k-means algorithms
TARSITANO, Agostino
2003-01-01
Abstract
The core of a k-means algorithm is the reallocation phase. A varietyof schemes have been suggested for moving entities from one cluster to another and each of them maygive a di(erent clustering even though the data set is the same. The present paper describes shortcomings and relative merits of 17 relocation methods in connection with randomlygenerated data sets.File in questo prodotto:
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