CLUSKEXT: CLUstering model for SKew-symmetric data including EXTernal information

Donatella Vicari ()
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Donatella Vicari: Sapienza University of Rome

Advances in Data Analysis and Classification, 2018, vol. 12, issue 1, No 4, 43-64

Abstract: Abstract A CLUstering model for SKew-symmetric data including EXTernal information (CLUSKEXT) is proposed, which relies on the decomposition of a skew-symmetric matrix into within and between cluster effects which are further decomposed into regression and residual effects when possible external information on the objects is available. In order to fit the imbalances between objects, the model jointly searches for a partition of objects and appropriate weights which are in turn linearly linked to the external variables. The proposal is fitted in a least-squares framework and a decomposition of the fit is derived. An appropriate Alternating Least-Squares algorithm is provided to fit the model to illustrative real and artificial data.

Keywords: Asymmetric data; Skew-symmetric matrix; Clustering; External information; 62H30; 91C20 (search for similar items in EconPapers)
Date: 2018
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DOI: 10.1007/s11634-015-0203-0

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