von Rosen, Dietrich
- Department of Energy and Technology, Swedish University of Agricultural Sciences
Research article2004Peer reviewed
Pavlenko Tatjana, Hall Mikael, von Rosen Dietrich, Andrushchenko Zhanna
We focus on Bayesian network (BN) classifiers and formalize the feature selection from a perspective of improving classification accuracy. To exploring the effect of high-dimensionality we apply the growing dimension asymptotics. We modify the weighted BN by introducing inclusion-exclusion factors which eliminate the features whose separation score do not exceed a given threshold. We establish the asymptotic optimal threshold and demonstrate that the proposed selection technique carries improvements over classification accuracy
Soft Methodology and Random Information Systems
2004, pages: 613-620
Publisher: Springer, Berlin
https://res.slu.se/id/publ/7268