Feature Selection by Maximizing Independent Classification Information

Volume: 29, Issue: 4, Pages: 828 - 841
Published: Apr 1, 2017
Abstract
Feature selection approaches based on mutual information can be roughly categorized into two groups. The first group minimizes the redundancy of features between each other. The second group maximizes the new classification information of features providing for the selected subset. A critical issue is that large new information does not signify little redundancy, and vice versa. Features with large new information but with high redundancy may be...
Paper Details
Title
Feature Selection by Maximizing Independent Classification Information
Published Date
Apr 1, 2017
Volume
29
Issue
4
Pages
828 - 841
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