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Bayesian Model Averaging Naive Bayes (BMA-NB): Averaging over an Exponential Number of Feature Models in Linear Time

Wu, Ga; Sanner, Scott; Oliveira, Rodrigo F.S.C.

Description

Naive Bayes (NB) is well-known to be a simple but effective classifier, especially when combined with feature selection. Unfortunately, feature selection methods are often greedy and thus cannot guarantee an optimal feature set is selected. An alternative to feature selection is to use Bayesian model averaging (BMA), which computes a weighted average over multiple predictors; when the different predictor models correspond to different feature sets, BMA has the advantage over feature selection...[Show more]

CollectionsANU Research Publications
Date published: 2015
Type: Conference paper
URI: http://hdl.handle.net/1885/103807
Source: HVAC-Aware Occupancy Scheduling

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