| Title: | 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. |
| URI: | http://hdl.handle.net/2451/33545 |
| Appears in Collections: | Center for Business Analytics Working Papers |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| wallenius.pdf | 317.45 kB | Adobe PDF | View/Open |
Items in FDA are protected by copyright, with all rights reserved, unless otherwise indicated.