A Neuroevolutionary Approach to Feature Selection Using Multiobjective Evolutionary Algorithms

[1]  Guy Lapalme,et al.  A systematic analysis of performance measures for classification tasks , 2009, Inf. Process. Manag..

[2]  Mengjie Zhang,et al.  Pareto front feature selection based on artificial bee colony optimization , 2018, Inf. Sci..

[3]  António Gaspar-Cunha,et al.  Neuroevolutionary Multiobjective Methodology for the Optimization of the Injection Blow Molding Process , 2019, EMO.

[4]  Jinbo Bi.  Multi-Objective Programming in SVMs , 2003, ICML.

[5]  Luiz Eduardo Soares de Oliveira,et al.  Feature Selection for Ensembles Using the Multi-Objective Optimization Approach , 2006, Multi-Objective Machine Learning.

[6]  Masoud Nikravesh,et al.  Feature Extraction - Foundations and Applications , 2006, Feature Extraction.

[7]  Alexandre C. B. Delbem,et al.  Neuroevolution for solving multiobjective knapsack problems , 2019, Expert Syst. Appl..

[8]  António Gaspar-Cunha,et al.  Feature Selection Using Multi-Objective Evolutionary Algorithms: Application to Cardiac SPECT Diagnosis , 2010, IWPACBB.

[9]  Ratna Babu Chinnam,et al.  mr2PSO: A maximum relevance minimum redundancy feature selection method based on swarm intelligence for support vector machine classification , 2011, Inf. Sci..

[10]  António Gaspar-Cunha,et al.  Evolving Neural Networks to Optimize Material Usage in Blow Molded Containers , 2018, Computational Methods in Applied Sciences.

[11]  Lothar Thiele,et al.  Multiobjective Optimization Using Evolutionary Algorithms - A Comparative Case Study , 1998, PPSN.

[12]  Christian Igel,et al.  Multi-objective Model Selection for Support Vector Machines , 2005, EMO.

[13]  Nicola Beume,et al.  SMS-EMOA: Multiobjective selection based on dominated hypervolume , 2007, Eur. J. Oper. Res..