A fast and recursive algorithm for clustering large datasets with -medians

Clustering with fast algorithms large samples of high dimensional data is an important challenge in computational statistics. A new class of recursive stochastic gradient algorithms designed for the k -medians loss criterion is proposed. By their recursive nature, these algorithms are very fast and...

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Veröffentlicht in:	Computational statistics & data analysis 2012-06, Vol.56 (6), p.1434-1449
Hauptverfasser:	Cardot, Hervé, Cénac, Peggy, Monnez, Jean-Marie
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Clustering Computation Partitioning Recursive Samples Statistical analysis Statistical methods
Online-Zugang:	Volltext
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