We discuss an extension of mixtures of factor analyzers (MFA) to allow for simultaneous clustering of subjects and variables where discrete manifest variables are available. To estimate model parameters, we propose a modified EM algorithm in a ML framework.
A biclustering approach for discrete outcomes / Martella, Francesca; Alfo', Marco. - (2013). ( 9th Scientific Meeting of the Classification and Data Analysis Group of the Italian Statistical Society 2013 Modena (Italy) September 2013).
A biclustering approach for discrete outcomes
MARTELLA, Francesca;ALFO', Marco
2013
Abstract
We discuss an extension of mixtures of factor analyzers (MFA) to allow for simultaneous clustering of subjects and variables where discrete manifest variables are available. To estimate model parameters, we propose a modified EM algorithm in a ML framework.File allegati a questo prodotto
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