A Feature Subset Selection Method Based On High-Dimensional Mutual Information

@article{Zheng2011AFS,
  title={A Feature Subset Selection Method Based On High-Dimensional Mutual Information},
  author={Yun Zheng and Chee Keong Kwoh},
  journal={Entropy},
  year={2011},
  volume={13},
  pages={860-901}
}
Feature selection is an important step in building accurate classifiers and provides better understanding of the data sets. In this paper, we propose a feature subset selection method based on high-dimensional mutual information. We also propose to use the entropy of the class attribute as a criterion to determine the appropriate subset of features when building classifiers. We prove that if the mutual information between a feature set X and the class attribute Y equals to the entropy of Y… CONTINUE READING
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