caa a22 4500 606159622 CHVBK 20210128100625.0 cr unu---uuuuu 210128e20150401xx s 000 0 eng 10.1007/s00521-014-1673-2 doi (NATIONALLICENCE)springer-10.1007/s00521-014-1673-2 Hybrid evolutionary algorithms for classification data mining [Elektronische Daten] [Mrutyunjaya Panda, Ajith Abraham] In this paper, we propose novel methods to find the best relevant feature subset using fuzzy rough set-based attribute subset selection with biologically inspired algorithm search such as ant colony and particle swarm optimization and the principles of an evolutionary process. We then propose a hybrid fuzzy rough with K-nearest neighbor (K-NN)-based classifier (FRNN) to classify the patterns in the reduced datasets, obtained from the fuzzy rough bio-inspired algorithm search. While exploring other possible hybrid evolutionary processes, we then conducted experiments considering (i) same feature selection algorithm with support vector machine (SVM) and random forest (RF) classifier; (ii) instance based selection using synthetic minority over-sampling technique with fuzzy rough K-nearest neighbor (K-NN), SVM and RF classifier. The proposed hybrid is subsequently validated using real-life datasets obtained from the University of California, Irvine machine learning repository. Simulation results demonstrate that the proposed hybrid produces good classification accuracy. Finally, parametric and nonparametric statistical tests of significance are carried out to observe consistency of the classifiers. The Natural Computing Applications Forum, 2014 Evolutionary algorithms nationallicence Fuzzy rough nationallicence Neural network nationallicence Bio-inspired algorithms nationallicence Classification nationallicence Statistical test nationallicence Panda Mrutyunjaya Gandhi Institute for Technological Advancement (GITA), 752054, Bhubaneswar, India aut Abraham Ajith Machine Intelligence Research Labs (MIR Labs), Scientific Network for Innovation and Research Excellence, P.O. Box 2259, 98071, Auburn, WA, USA aut Neural Computing and Applications Springer London 26/3(2015-04-01), 507-523 0941-0643 26:3<507 2015 26 521 https://doi.org/10.1007/s00521-014-1673-2 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00521-014-1673-2 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Panda Mrutyunjaya Gandhi Institute for Technological Advancement (GITA), 752054, Bhubaneswar, India aut NATIONALLICENCE 700 1- Abraham Ajith Machine Intelligence Research Labs (MIR Labs), Scientific Network for Innovation and Research Excellence, P.O. Box 2259, 98071, Auburn, WA, USA aut NATIONALLICENCE 773 0- Neural Computing and Applications Springer London 26/3(2015-04-01), 507-523 0941-0643 26:3<507 2015 26 521