Full metadata record
DC Field | Value | Language |
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dc.contributor.author | Junque de Fortuny, Enric | - |
dc.contributor.author | Martens, David | - |
dc.contributor.author | Provost, Foster | - |
dc.date.accessioned | 2013-12-20T21:21:39Z | - |
dc.date.available | 2013-12-20T21:21:39Z | - |
dc.date.issued | 2013-12-20 | - |
dc.identifier.uri | http://hdl.handle.net/2451/33545 | - |
dc.description.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. | en_US |
dc.description.sponsorship | Faculty of Applied Economics, University of Antwerp, Belgium; Department of Information, Operations & Management Sciences, NYU Stern School of Business | en_US |
dc.language.iso | en_US | en_US |
dc.relation.ispartofseries | CBA-13-05 | - |
dc.title | Wallenius Naive Bayes | en_US |
dc.type | Working Paper | en_US |
Appears in Collections: | Center for Business Analytics Working Papers |
Files in This Item:
File | Description | Size | Format | |
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wallenius.pdf | 317.45 kB | Adobe PDF | View/Open |
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