Reference-point-based multi-objective optimization algorithm with opposition-based voting scheme for multi-label feature selection

DOI10.1016/j.ins.2020.08.004zbMath1475.68261OpenAlexW3047822990MaRDI QIDQ2056267

Shahryar Rahnamayan, Azam Asilian Bidgoli, Hossein Ebrahimpour-Komleh

Publication date: 2 December 2021

Published in: Information Sciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ins.2020.08.004

zbMATH Keywords

multi-objective optimizationevolutionary algorithmfeature selectionmulti-label classificationopposition-based computation

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Evolutionary algorithms, genetic algorithms (computational aspects) (68W50) Multi-objective and goal programming (90C29) Learning and adaptive systems in artificial intelligence (68T05) Approximation methods and heuristics in mathematical programming (90C59)

Related Items

Multi-label feature selection based on the division of label topics

Uses Software

• MOEA/D
• SPEA2
• MULAN
• ML-KNN

Cites Work

• ML-KNN: A lazy learning approach to multi-label learning
• Running time analysis of evolutionary algorithms on a simplified multiobjective knapsack problem
• 10.1162/153244303322753616
• Unnamed Item