A hybrid genetic algorithm for feature selection wrapper based on mutual information

By Jinjie Huang, Yunze Cai, Xiaoming Xu. Pattern Recognition Letters, 2007

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An advanced ACO algorithm for feature subset selection (2015, background): “Filter and wrapper are two complementary approaches, then the hybrid approach attempts to take advantage of the filter and wrapper approaches by exploiting their complementary strengths [33, 15, 36].”
mr2PSO: A maximum relevance minimum redundancy feature selection method based on swarm intelligence for support vector machine classification (2011, background): “Besides their comparative computational efficiency, there are other compelling arguments for using filter methods.”
BBA: A Binary Bat Algorithm for Feature Selection (2012, background): “In addition, several works have addressed the same problem with a wide range of nature-inspired techniques [9], [10], [11].”
A Survey on Evolutionary Computation Approaches to Feature Selection (2016, methodology): “Similarly, local search for filter feature selection using mutual information was applied together with GAs and PSO for wrapper feature selection to develop memetic approaches in [50], [176], and [228].”
Supervised hybrid feature selection based on PSO and rough sets for medical diagnosis (2014, background): “Many supervised machine learning tasks can be transmitted as the problem of assigning elements to a finite set of classes or categories [5,6].”