Reconsidering Mutual Information Based Feature Selection: A Statistical Significance View
Xuan Vinh Nguyen, Jeffrey Chan, James Bailey
Proceedings of the National Conference on Artificial Intelligence | ASSOC ADVANCEMENT ARTIFICIAL INTELLIGENCE | Published : 2014
Copyright © 2014, Association for the Advancement of Artificial Intelligence. Mutual information (MI) based approaches are a popular feature selection paradigm. Although the stated goal of Mi-based feature selection is to identify a subset of features that share the highest mutual information with the class variable, most current Mi-based techniques are greedy methods that make use of low dimensional MI quantities. The reason for using low dimensional approximation has been mostly attributed to the difficulty associated with estimating the high dimensional MI from limited samples. In this paper, we argue a different viewpoint that, given a very large amount of data, the high dimensional MI o..View full abstract
Awarded by Australian Research Council
This work is supported by the Australian Research Council via grant number FT110100112.