Integer Bayesian Network Classifiers
Abstract
This paper introduces integer Bayesian network classifiers (BNCs), i.e. BNCs with discrete valued nodes where parameters are stored as integer numbers. These networks allow for efficient implementation in hardware while maintaining a (partial) probabilistic interpretation under scaling. An algorithm for the computation of margin maximizing integer parameters is presented and its efficiency is demonstrated. The resulting parameters have superior classification performance compared to parameters obtained by simple rounding of double-precision parameters, particularly for very low number of bits.
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- Tschiatschek, Sebastian
- Paul, Karin
- Pernkopf, Franz
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Shortfacts
Category |
Paper in Conference Proceedings or in Workshop Proceedings (Paper) |
Event Title |
European Conference on Machine Learning and Knowledge Discovery in Databases (ECML PKDD) |
Divisions |
Data Mining and Machine Learning |
Event Location |
Nancy, France |
Event Type |
Conference |
Event Dates |
15.-19.09.2014 |
Series Name |
Machine Learning and Knowledge Discovery in Databases. ECML PKDD 2014. Lecture Notes in Computer Science |
ISSN/ISBN |
978-3-662-44844-1 |
Page Range |
pp. 209-224 |
Date |
15 September 2014 |
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