New methodologies for two-mode (objects and variables) multi-partitioning of two way data are presented. In particular, by reanalyzing the double k-means, that identifies a unique partition for each mode of the data, a relevant extension is discussed which allows to specify more partitions of one mode, conditionally to the partition of the other one. The performance of such generalized double k-means has been tested by both a simulation study and an application to gene microarray data.
Rocci, R., Vichi, M. (2008). Two-mode multi-partitioning. COMPUTATIONAL STATISTICS & DATA ANALYSIS, 52(4), 1984-2003 [10.1016/j.csda.2007.06.025].
Two-mode multi-partitioning
ROCCI, ROBERTO;
2008-01-01
Abstract
New methodologies for two-mode (objects and variables) multi-partitioning of two way data are presented. In particular, by reanalyzing the double k-means, that identifies a unique partition for each mode of the data, a relevant extension is discussed which allows to specify more partitions of one mode, conditionally to the partition of the other one. The performance of such generalized double k-means has been tested by both a simulation study and an application to gene microarray data.| File | Dimensione | Formato | |
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2008 RocciVichiTwoModeMultiPartitioning.pdf
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Descrizione: Articolo su CSDA 2008
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