caa a22 4500 606160337 CHVBK 20210128100629.0 cr unu---uuuuu 210128e20150201xx s 000 0 eng 10.1007/s00521-014-1632-y doi (NATIONALLICENCE)springer-10.1007/s00521-014-1632-y Probabilistic ensemble Fuzzy ARTMAP optimization using hierarchical parallel genetic algorithms [Elektronische Daten] [Chu Loo, Wei Liew, Manjeevan Seera, Einly Lim] In this study, a comprehensive methodology for overcoming the design problem of the Fuzzy ARTMAP neural network is proposed. The issues addressed are the sequence of training data for supervised learning and optimum parameter tuning for parameters such as baseline vigilance. A genetic algorithm search heuristic was chosen to solve this multi-objective optimization problem. To further augment the ARTMAP's pattern classification ability, multiple ARTMAPs were optimized via genetic algorithm and assembled into a classifier ensemble. An optimal ensemble was realized by the inter-classifier diversity of its constituents. This was achieved by mitigating convergence in the genetic algorithms by employing a hierarchical parallel architecture. The best-performing classifiers were then combined in an ensemble, using probabilistic voting for decision combination. This study also integrated the disparate methods to operate within a single framework, which is the proposed novel method for creating an optimum classifier ensemble configuration with minimum user intervention. The methodology was benchmarked using popular data sets from UCI machine learning repository. Springer-Verlag London, 2014 Ensembles nationallicence Fuzzy ARTMAP nationallicence Plurality voting nationallicence Parallel genetic algorithm nationallicence Feature selection nationallicence Loo Chu Faculty of Computer Science and Information Technology, University Malaya, Kuala Lumpur, Malaysia aut Liew Wei Faculty of Computer Science and Information Technology, University Malaya, Kuala Lumpur, Malaysia aut Seera Manjeevan Faculty of Computer Science and Information Technology, University Malaya, Kuala Lumpur, Malaysia aut Lim Einly Faculty of Biomedical Engineering, University Malaya, Kuala Lumpur, Malaysia aut Neural Computing and Applications Springer London 26/2(2015-02-01), 263-276 0941-0643 26:2<263 2015 26 521 https://doi.org/10.1007/s00521-014-1632-y 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/s00521-014-1632-y text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Loo Chu Faculty of Computer Science and Information Technology, University Malaya, Kuala Lumpur, Malaysia aut NATIONALLICENCE 700 1- Liew Wei Faculty of Computer Science and Information Technology, University Malaya, Kuala Lumpur, Malaysia aut NATIONALLICENCE 700 1- Seera Manjeevan Faculty of Computer Science and Information Technology, University Malaya, Kuala Lumpur, Malaysia aut NATIONALLICENCE 700 1- Lim Einly Faculty of Biomedical Engineering, University Malaya, Kuala Lumpur, Malaysia aut NATIONALLICENCE 773 0- Neural Computing and Applications Springer London 26/2(2015-02-01), 263-276 0941-0643 26:2<263 2015 26 521