On the use of Bernoulli mixture models for text classification

DOI10.1016/S0031-3203(01)00242-4zbMath1010.68154OpenAlexW1987307590MaRDI QIDQ1856679

Yanyan Li

Publication date: 11 February 2003

Published in: Pattern Recognition (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0031-3203(01)00242-4

zbMATH Keywords

EM algorithmtext classificationmixture modelsmultivariate Bernoulli distributionmultivariate binary datadata categorization

Mathematics Subject Classification ID

Pattern recognition, speech recognition (68T10)

Related Items (6)

Estimators and D-optimal experimental designs for mixtures of binary responses ⋮ A generalized bivariate Bernoulli model with covariate dependence ⋮ On multivariate binary data clustering and feature weighting ⋮ Efficient mixture model for clustering of sparse high dimensional binary data ⋮ Discrete data clustering using finite mixture models ⋮ Unnamed Item

Cites Work

• Text classification from labeled and unlabeled documents using EM
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