A new Feature Reduction Algorithm Based on Fuzzy Rough Relation for the Multi-label Classification

Abstract

The paper aims to improve the multi-label classification performance using the feature reduction technique. According to the determination of the dependency among features based on fuzzy rough relation, features with the highest dependency score will be retained in the reduction set. The set is subsequently applied to enhance the performance of the multi-label classifier. We investigate the effectiveness of the proposed model againts the baseline via time complexity.

Keywords:

Fuzzy rough relation, label-specific feature, feature reduction set

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