An evolutionary framework using particle swarm optimization for classification method PROAFTN

2010 Al-Obeidat, 2010, Automatic parameter settings for the PROAFTN classifier using hybrid particle swarm optimization, 184 Al-Obeidat, 2010, Differential evolution for learning the classification method PROAFTN, Knowledge-Based Systems, 23, 418, 10.1016/j.knosys.2010.02.003 Alpaydin, 2004 A. Asuncion, D.J. Newman, UCI Machine Learning Repository, 2007. Baim, 1988, A method for attribute selection in inductive learning systems, IEEE Transactions on Pattern Analysis and Machine Intelligence, 10, 888, 10.1109/34.9110 N. Belacel, Multicriteria Classification Methods: Methodology and Medical Applications, PhD thesis, Free University of Brussels, Belgium, 1999. Belacel, 2000, Multicriteria assignment method PROAFTN: methodology and medical application, European Journal of Operational Research, 125, 175, 10.1016/S0377-2217(99)00192-7 Belacel, 2001, Multicriteria fuzzy assignment method: a useful tool to assist medical diagnosis, Artificial Intelligence in Medicine, 21, 201, 10.1016/S0933-3657(00)00086-5 Belacel, 2007, Learning multicriteria fuzzy classification method PROAFTN from data, Computers and Operations Research, 34, 1885, 10.1016/j.cor.2005.07.019 Belacel, 2005, Web-integration of PROAFTN methodology for acute leukemia diagnosis, Telemedicine Journal and e-Health, 11, 652, 10.1089/tmj.2005.11.652 Bouyssou, 2000 Burges, 1998, A tutorial on support vector machines for pattern recognition, Data Mining and Knowledge Discovery, 2, 1, 10.1023/A:1009715923555 Cai, 2007, Time series prediction with recurrent neural networks trained by a hybrid PSO-EA algorithm, Neurocomputing, 70, 2342, 10.1016/j.neucom.2005.12.138 Castellano, 1997, An iterative pruning algorithm for feedforward neural networks, IEEE Transactions on Neural Networks, 8, 519, 10.1109/72.572092 Chang, 2009, A PSO method with nonlinear time-varying evolution based on neural network for design of optimal harmonic filters, Expert Systems with Applications, 36, 6809, 10.1016/j.eswa.2008.08.007 Clerc, 2002, The particle swarm – explosion, stability, and convergence in a multidimensional complex space, IEEE Transactions on Evolutionary Computation, 6, 58, 10.1109/4235.985692 Cooper, 1992, A Bayesian method for the induction of probabilistic networks from data, Machine Learning, 9, 309, 10.1007/BF00994110 Demšar, 2006, Statistical comparisons of classifiers over multiple data sets, Journal of Machine Learning Research., 7, 1 Dias, 2002, An aggregation/disaggregation approach to obtain robust conclusions with ELECTRE tri, European Journal of Operational Research, 138, 332, 10.1016/S0377-2217(01)00250-8 Dutton, 1996, A review of machine learning, The Knowledge Engineering Review, 12, 341, 10.1017/S026988899700101X Eberhart, 1995, New optimizer using particle swarm theory, 39 Eberhart, 1995, Particle swarm optimization, 1942 De Falco, 2007, Facing classification problems with particle swarm optimization, Applied Soft Computing, 7, 652, 10.1016/j.asoc.2005.09.004 Garcia, 2009, An extension on “statistical comparisons of classifiers over multiple data sets” for all pairwise comparisons, Journal of Machine Learning Research, 9, 2677 Güngör, 2009, A fuzzy AHP approach to personnel selection problem, Applied Soft Computing, 9, 641, 10.1016/j.asoc.2008.09.003 Goebel, 1999, A survey of data mining and knowledge discovery software tools, SIGKDD Explorations Newsletter, 1, 20, 10.1145/846170.846172 Holden, 2007, A hybrid PSO/ACO algorithm for classification Hu, 2003, Swarm intelligence for permutation optimization: a case study of n-queens problem, 243 Jabeur, 2007, A generalized framework for concordance/discordance-based multi-criteria classification methods, 1 Kennedy, 2001 Léger, 2002, A multi-criteria assignment procedure for a nominal sorting problematic, European Journal of Operational Research, 138, 349, 10.1016/S0377-2217(01)00251-X Lidouh, 2009, Circular representations of a valued preference matrix, 261, 10.1007/978-3-642-04428-1_23 Lin, 2009, PSOLDA: a particle swarm optimization approach for enhancing classification accuracy rate of linear discriminant analysis, Applied Soft Computing, 9, 1008, 10.1016/j.asoc.2009.01.001 Mitchell, 1997 Pang, 2005, Face membership authentication using SVM classification tree generated by membership-based lle data partition, IEEE Transactions on Neural Networks, 16, 436, 10.1109/TNN.2004.841776 Poli, 2008, Analysis of the publications on the applications of particle swarm optimisation, Journal of Artificial Evolution and Applications, 8, 1, 10.1155/2008/685175 Quinlan, 1996, Improved use of continuous attributes in C4.5, Journal of Artificial Intelligence Research, 4, 77, 10.1613/jair.279 Roy, 1996 Salman, 2002, Particle swarm optimization for task assignment problem, Microprocessors and Microsystems, 26, 363, 10.1016/S0141-9331(02)00053-4 Schutte, 2005, A study of global optimization using particle swarms, Journal of Global Optimization, 31, 93, 10.1007/s10898-003-6454-x Shirvany, 2009, Multilayer perceptron neural networks with novel unsupervised training method for numerical solution of the partial differential equations, Applied Soft Computing., 9, 20, 10.1016/j.asoc.2008.02.003 Smyth, 2002, Data-driven evolution of data mining algorithms, Communications of the ACM, 45, 33, 10.1145/545151.545175 Sousa, 2004, Particle swarm based data mining algorithms for classification tasks, Parallel Computing, 30, 767, 10.1016/j.parco.2003.12.015 Subramanian, 2003, Knowledge-based association rule mining using and–or taxonomies, Knowledge-Based Systems, 16, 37, 10.1016/S0950-7051(02)00050-3 B. Twala, Multiple classifier application to credit risk assessment, Expert Systems with Applications 37 (4) (2010) 3326–3336. van den Bergh, 2006, A study of particle swarm optimization particle trajectories, Information Sciences, 176, 937, 10.1016/j.ins.2005.02.003 Vasant, 2007, Detection of level of satisfaction and fuzziness patterns for MCDM model with modified flexible s-curve mf, Applied Soft Computing, 7, 1044, 10.1016/j.asoc.2006.10.005 Xu, 2009, Knowledge granulation, knowledge entropy and knowledge uncertainty measure in ordered information systems, Applied Soft Computing, 9, 1244, 10.1016/j.asoc.2009.03.007 Weiss, 1991 Witten, 2005 Yoshida, 2000, A particle swarm optimization for reactive power and voltage control considering voltage security assessment, IEEE Transactions on Power Systems, 15, 1232, 10.1109/59.898095 Zhang, 2008, Decision support in cancer base on fuzzy adaptive PSO for feedforward neural network training Zopounidis, 2002, Multicriteria classification and sorting methods: a literature review, European Journal of Operational Research, 138, 229, 10.1016/S0377-2217(01)00243-0