MIARS: Mutual information-guided feature selection with angle reconstruction and semantic alignment for multi-label learning

Key Points

• Effective feature selection is guided by mutual information, enhancing learning outcomes.
• Semantic alignment plays a crucial role in ensuring relevant feature integration during analysis.
• Angle reconstruction facilitates the understanding of complex relationships between data features.
• The method demonstrates significant potential for application across various machine learning tasks.