When is the naive Bayes approximation not so naive?

DOI10.1007/S10994-017-5658-0zbMath1458.62131OpenAlexW2736889870MaRDI QIDQ1707489

Ana Ruíz Linares, Christopher R. Stephens, Hugo Flores Huerta

Publication date: 3 April 2018

Published in: Machine Learning (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10994-017-5658-0

zbMATH Keywords

classificationerror analysisperformance predictiongeneralized Bayes approximationnaive Bayes approximation

Mathematics Subject Classification ID

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

Related Items (1)

Clustering Data with Nonignorable Missingness using Semi-Parametric Mixture Models

Cites Work

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• Learning by extrapolation from marginal to full-multivariate probability distributions: Decreasingly naive Bayesian classification
• Bayesian network classifiers
• Not so naive Bayes: Aggregating one-dependence estimators
• Markov Random Fields and Their Applications
• Naive Bayes for optimal ranking
• Machine Learning: ECML 2004

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