A CLUstering model for SKew-symmetric data including EXTernal information (CLUSKEXT) is proposed, which relies on the decomposition of a skewsymmetric 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.

CLUSKEXT: CLUstering model for SKew-symmetric data including EXTernal information / Vicari, Donatella. - In: ADVANCES IN DATA ANALYSIS AND CLASSIFICATION. - ISSN 1862-5347. - STAMPA. - 12:1(2018), pp. 43-64. [10.1007/s11634-015-0203-0]

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

VICARI, Donatella
2018

Abstract

A CLUstering model for SKew-symmetric data including EXTernal information (CLUSKEXT) is proposed, which relies on the decomposition of a skewsymmetric 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.
2018
asymmetric data; skew-symmetric matrix; clustering; external information
01 Pubblicazione su rivista::01a Articolo in rivista
CLUSKEXT: CLUstering model for SKew-symmetric data including EXTernal information / Vicari, Donatella. - In: ADVANCES IN DATA ANALYSIS AND CLASSIFICATION. - ISSN 1862-5347. - STAMPA. - 12:1(2018), pp. 43-64. [10.1007/s11634-015-0203-0]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/779613
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