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Text document classification based on mixture models

Jana Novovičová, Antonín Malík (2004)

Kybernetika

Finite mixture modelling of class-conditional distributions is a standard method in a statistical pattern recognition. This paper, using bag-of-words vector document representation, explores the use of the mixture of multinomial distributions as a model for class-conditional distribution for multiclass text document classification task. Experimental comparison of the proposed model and the standard Bernoulli and multinomial models as well as the model based on mixture of multivariate Bernoulli distributions...

The likelihood ratio test for general mixture models with or without structural parameter

Jean-Marc Azaïs, Élisabeth Gassiat, Cécile Mercadier (2009)

ESAIM: Probability and Statistics

This paper deals with the likelihood ratio test (LRT) for testing hypotheses on the mixing measure in mixture models with or without structural parameter. The main result gives the asymptotic distribution of the LRT statistics under some conditions that are proved to be almost necessary. A detailed solution is given for two testing problems: the test of a single distribution against any mixture, with application to Gaussian, Poisson and binomial distributions; the test of the number of populations...

The likelihood ratio test for the number of components in a mixture with Markov regime

Elisabeth Gassiat, Christine Keribin (2010)

ESAIM: Probability and Statistics

We study the LRT statistic for testing a single population i.i.d. model against a mixture of two populations with Markov regime. We prove that the LRT statistic converges to infinity in probability as the number of observations tends to infinity. This is a consequence of a convergence result of the LRT statistic for a subproblem where the parameters are restricted to a subset of the whole parameter set.

Theory of classification : a survey of some recent advances

Stéphane Boucheron, Olivier Bousquet, Gábor Lugosi (2005)

ESAIM: Probability and Statistics

The last few years have witnessed important new developments in the theory and practice of pattern classification. We intend to survey some of the main new ideas that have led to these recent results.

Theory of Classification: a Survey of Some Recent Advances

Stéphane Boucheron, Olivier Bousquet, Gábor Lugosi (2010)

ESAIM: Probability and Statistics

The last few years have witnessed important new developments in the theory and practice of pattern classification. We intend to survey some of the main new ideas that have led to these recent results.

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