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.
| Original language | English |
|---|---|
| Title of host publication | - |
| Publication status | In preparation - 2019 |
Research programs
- RSM MKT
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