Unsupervised learning of finite mixture models

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Unsupervised learning of finite mixture models (2002)

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by Mario A. T. Figueiredo , Anil K. Jain

Venue:	IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
Citations:	412 - 22 self

BibTeX

@ARTICLE{Figueiredo02unsupervisedlearning,
    author = {Mario A. T. Figueiredo and Anil K. Jain},
    title = {Unsupervised learning of finite mixture models},
    journal = {IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE},
    year = {2002},
    volume = {24},
    number = {3},
    pages = {381--396}
}

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Abstract

This paper proposes an unsupervised algorithm for learning a finite mixture model from multivariate data. The adjective ªunsupervisedº is justified by two properties of the algorithm: 1) it is capable of selecting the number of components and 2) unlike the standard expectation-maximization (EM) algorithm, it does not require careful initialization. The proposed method also avoids another drawback of EM for mixture fitting: the possibility of convergence toward a singular estimate at the boundary of the parameter space. The novelty of our approach is that we do not use a model selection criterion to choose one among a set of preestimated candidate models; instead, we seamlessly integrate estimation and model selection in a single algorithm. Our technique can be applied to any type of parametric mixture model for which it is possible to write an EM algorithm; in this paper, we illustrate it with experiments involving Gaussian mixtures. These experiments testify for the good performance of our approach.

Keyphrases

finite mixture model model selection parameter space good performance unsupervised algorithm preestimated candidate model bayesian method expectation-maximization algorithm unsupervised learning parametric mixture model gaussian mixture single algorithm careful initialization index term finite mixture mixture fitting multivariate data standard expectation-maximization em algorithm minimum message length criterion model selection criterion singular estimate

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