alexa Idiot's Bayes: Not So Stupid after All?
Biomedical Sciences

Biomedical Sciences

International Journal of Biomedical Data Mining

Author(s): David J Hand, Keming Yu

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Folklore has it that a very simple supervised classification rule, based on the typically false assumption that the predictor variables are independent, can be highly effective, and often more effective than sophisticated rules. We examine the evidence for this, both empirical, as observed in real data applications, and theoretical, summarising explanations for why this simple rule might be effective. /// La tradition veut qu'une règle très simple assumant l'independance des variables prédictives, une hypothèse fausse dans la plupart des cas, peut être très efficace, souvent même plus efficace qu'une méthode plus sophistiquée en ce qui concerne l'attribution de classes a un groupe d'objects. A ce sujet, nous examinons les preuves empiriques, observées sur des données réelles, et les preuves théoriques, c'est-a-dire les raisons pour lesquelles cette simple règle pourrait faciliter le processus de tri.

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This article was published in International Statistical Review / Revue Internationale de Statistique and referenced in International Journal of Biomedical Data Mining

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