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Constrained domain maximum likelihood estimation for naive Bayes text classification

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Publication:710635
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DOI10.1007/s10044-009-0149-yzbMath1426.62179OpenAlexW1973898298MaRDI QIDQ710635

Jesús Andrés-Ferrer, Alfons Juan

Publication date: 19 October 2010

Published in: PAA. Pattern Analysis and Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10044-009-0149-y


zbMATH Keywords

maximum likelihood estimationKarush-Kuhn-Tucker conditionsnaive Bayestext classificationparameter smoothing


Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Bayesian inference (62F15)


Related Items (2)

Learning a flexible \(K\)-dependence Bayesian classifier from the chain rule of joint probability distribution ⋮ On the smoothing of multinomial estimates using Liouville mixture models and applications


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  • Bow


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