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Maximum relevant minimum redundant multi-label feature selection using ant colony optimization
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DOI：10.1016/j.engappai.2025.112007.png)
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Abstract
En 中文
• A filter-based multi-label feature selection method using ACO is proposed. • Feature space is mapped to a multi-layer graph for efficient search. • A modified ACO strategy was proposed to balance between local and global search. • An information-theoretic metric evaluates feature subsets without the need for classifiers. • Computational efficiency is enhanced via a two-layered graph structure.
Keywords:
Feature selection
Multi-label data
Mutual information
Graph clustering
Ant colony optimization
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