Chunking and cooperation in particle swarm optimization for feature selection

Abstract Bio-inspired optimization aims at adapting observed natural behavioral patterns and social phenomena towards efficiently solving complex problems, is nowadays gaining much attention. However, researchers recently highlighted an inconsistency between the need in field actual trend. Indeed, while it important to design innovative contributions, trend bio-inspired re-iterate existing knowledge a different form. The aim of this paper fill gap. More precisely, we start first by highlighting new examples for problem considering describing concepts chunking cooperative learning. Second, particle swarm (PSO), present novel bridge these two notions adapted feature selection. In experiments, investigate practical importance our approach exploring both its strength limitations. results indicate that mainly suitable large datasets, further research needed improve computational efficiency ensure independence sub-problems defined using chunking.