A multi-objective genetic algorithm for simultaneous model and feature selection for support vector machines
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[1] Xin Yao,et al. A Survey on Evolutionary Computation Approaches to Feature Selection , 2016, IEEE Transactions on Evolutionary Computation.
[2] Zhi Chen,et al. A Parallel Genetic Algorithm Based Feature Selection and Parameter Optimization for Support Vector Machine , 2016, Sci. Program..
[3] Yi-Hung Huang,et al. Feature Selection and Parameter Optimization of Support Vector Machines Based on Modified Cat Swarm Optimization , 2015, Int. J. Distributed Sens. Networks.
[4] Fong-Ching Yuan. Parameters Optimization Using Genetic Algorithms in Support Vector Regression for Sales Volume Forecasting , 2012 .
[5] Mingtian Zhou,et al. Feature selection and parameter optimization for support vector machines: A new approach based on genetic algorithm with feature chromosomes , 2011, Expert Syst. Appl..
[6] Christian Dipl.-Ing. Walther,et al. Parameter optimization for support vector machines by using a multicriteria genetic algorithm for classification of sleep-stages , 2010 .
[7] Ming-Chi Lee,et al. Using support vector machine with a hybrid feature selection method to the stock trend prediction , 2009, Expert Syst. Appl..
[8] Chih-Hung Wu,et al. A Novel hybrid genetic algorithm for kernel function and parameter optimization in support vector regression , 2009, Expert Syst. Appl..
[9] Huanhuan Chen,et al. Evolving Least Squares Support Vector Machines for Stock Market Trend Mining , 2009, IEEE Trans. Evol. Comput..
[10] Shih-Wei Lin,et al. Particle swarm optimization for parameter determination and feature selection of support vector machines , 2008, Expert Syst. Appl..
[11] Farid Melgani,et al. Classification of Electrocardiogram Signals With Support Vector Machines and Particle Swarm Optimization , 2008, IEEE Transactions on Information Technology in Biomedicine.
[12] Kalyanmoy Deb,et al. Omni-optimizer: A generic evolutionary algorithm for single and multi-objective optimization , 2008, Eur. J. Oper. Res..
[13] Ashutosh,et al. Evolutionary Selection of Kernels in Support Vector Machines , 2006, 2006 International Conference on Advanced Computing and Communications.
[14] Cheng-Lung Huang,et al. A GA-based feature selection and parameters optimizationfor support vector machines , 2006, Expert Syst. Appl..
[15] Delmiro Fernandez-Reyes,et al. Adapting multiple kernel parameters for support vector machines using genetic algorithms , 2005, 2005 IEEE Congress on Evolutionary Computation.
[16] Shuang Liu,et al. A new weighted support vector machine with GA-based parameter selection , 2005, 2005 International Conference on Machine Learning and Cybernetics.
[17] Yao-Nan Wang,et al. A method to choose kernel function and its parameters for support vector machines , 2005, 2005 International Conference on Machine Learning and Cybernetics.
[18] M. Pardo,et al. Classification of electronic nose data with support vector machines , 2005 .
[19] Kezhi Mao,et al. Feature subset selection for support vector machines through discriminative function pruning analysis , 2004, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).
[20] Bernhard Schölkopf,et al. Feature selection for support vector machines by means of genetic algorithm , 2003, Proceedings. 15th IEEE International Conference on Tools with Artificial Intelligence.
[21] Chih-Jen Lin,et al. Asymptotic Behaviors of Support Vector Machines with Gaussian Kernel , 2003, Neural Computation.
[22] Isabelle Guyon,et al. An Introduction to Variable and Feature Selection , 2003, J. Mach. Learn. Res..
[23] Chih-Jen Lin,et al. Radius Margin Bounds for Support Vector Machines with the RBF Kernel , 2002, Neural Computation.
[24] Xing Li,et al. Evolving support vector machine parameters , 2002, Proceedings. International Conference on Machine Learning and Cybernetics.
[25] Liu Fang,et al. Choosing multiple parameters for SVM based on genetic algorithm , 2002, 6th International Conference on Signal Processing, 2002..
[26] Kalyanmoy Deb,et al. A fast and elitist multiobjective genetic algorithm: NSGA-II , 2002, IEEE Trans. Evol. Comput..
[27] Sayan Mukherjee,et al. Choosing Multiple Parameters for Support Vector Machines , 2002, Machine Learning.
[28] Chih-Jen Lin,et al. A comparison of methods for multiclass support vector machines , 2002, IEEE Trans. Neural Networks.
[29] Kalyanmoy Deb,et al. Self-Adaptive Genetic Algorithms with Simulated Binary Crossover , 2001, Evolutionary Computation.
[30] Guoqiang Peter Zhang,et al. Neural networks for classification: a survey , 2000, IEEE Trans. Syst. Man Cybern. Part C.
[31] Anil K. Jain,et al. Dimensionality reduction using genetic algorithms , 2000, IEEE Trans. Evol. Comput..
[32] John C. Platt,et al. Fast training of support vector machines using sequential minimal optimization, advances in kernel methods , 1999 .
[33] Jihoon Yang,et al. Feature Subset Selection Using a Genetic Algorithm , 1998, IEEE Intell. Syst..
[34] Kunlun Li,et al. Parameter Optimization for Support Vector Machine Based on Nested Genetic Algorithms , 2015 .
[35] Andy,et al. Optimization Features Using GA-SVM Approach , 2015 .
[36] Aixia Guo,et al. Gene Selection for Cancer Classification using Support Vector Machines , 2014 .
[37] Zhang Hongtao,et al. Chaos Optimization Method of SVM Parameters Selection for Chaotic Time Series Forecasting , 2012 .
[38] J. Rajapakse,et al. Gene Classification Using Codon Usage and Support Vector Machines , 2009, IEEE/ACM Transactions on Computational Biology & Bioinformatics.
[39] S. Balakrishnan,et al. Feature Selection Using FCBF in Type II Diabetes Databases , 2009 .
[40] Ioannis Pitas,et al. Facial Expression Recognition in Image Sequences Using Geometric Deformation Features and Support Vector Machines , 2007, IEEE Transactions on Image Processing.
[41] Chih-Jen Lin,et al. Feature Extraction, Foundations and Applications , 2006 .
[42] Holger Frohlich,et al. Feature Selection for Support Vector Machines by Means of Genetic Algorithms -Diploma Thesis in Computer Science- , 2002 .
[43] Vladimir N. Vapnik,et al. The Nature of Statistical Learning Theory , 2000, Statistics for Engineering and Information Science.
[44] Marco Sciandrone,et al. Please Scroll down for Article Optimization Methods and Software Feature Selection Combining Linear Support Vector Machines and Concave Optimization Feature Selection Combining Linear Support Vector Machines and Concave Optimization , 2022 .