The EM Algorithm for Mixtures of Factor Analyzers
Zoubin Ghahramani and Geoffrey E. Hinton
Department of Computer Science
University of Toronto
Technical Report CRG-TR-96-1
Abstract
Factor analysis, a statistical method for modeling the covariance
structure of high dimensional data using a small number of latent variables, can be
extended by allowing different local factor models in different regions of the input
space. This results in a model which concurrently performs clustering and
dimensionality reduction, and can be thought of as a reduced dimension mixture of
Gaussians. We present an exact Expectation-maximization algorithm for fitting the
parameters of this mixture of factor analyzers.
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