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Wallenius Naive Bayes

Authors: Junque de Fortuny, Enric
Martens, David
Provost, Foster
Issue Date: 20-Dec-2013
Series/Report no.: CBA-13-05
Abstract: Traditional event models underlying naive Bayes classifiers assume probability distributions that are not appropriate for binary data generated by human behaviour. In this work, we develop a new event model, based on a somewhat forgotten distribution created by Kenneth Ted Wallenius in 1963. We show that it achieves superior performance using less data on a collection of Facebook datasets, where the task is to predict personality traits, based on likes.
Appears in Collections:Center for Business Analytics Working Papers

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