Averaged Naive Bayes Trees: A New Extension of AODE
作者： Mori Kurokawa , Hiroyuki Yokoyama , Akito Sakurai
DOI: 10.1007/978-3-642-05224-8_16
关键词:
摘要: Naive Bayes (NB) is a simple Bayesian classifier that assumes the conditional independence and augmented NB (ANB) models are extensions of by relaxing assumption. The averaged one-dependence estimators (AODE) averages ODEs, which ANB models. However, expressiveness AODE still limited restricted structure ODE. In this paper, we propose model averaging method for Trees (NBTs) with flexible structures present experimental results in terms classification accuracy. Results comparative experiments show our proposed outperforms on
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