Optimal Hyper-Parameter Tuning of SVM Classifiers With Application to Medical Diagnosis
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Alfonso Rojas-Domínguez | Luis Carlos Padierna | Juan Martín Carpio Valadez | Hector J. Puga-Soberanes | Héctor J. Fraire | H. J. Puga-Soberanes | L. C. Padierna | Alfonso Rojas-Domínguez | Héctor Fraire | J. M. Carpio Valadez
[1] Ming-Huwi Horng,et al. The Construction of Support Vector Machine Classifier Using the Firefly Algorithm , 2015, Comput. Intell. Neurosci..
[2] Shih-Wei Lin,et al. Particle swarm optimization for parameter determination and feature selection of support vector machines , 2008, Expert Syst. Appl..
[3] S. Ivvan Valdez,et al. A Boltzmann based estimation of distribution algorithm , 2013 .
[4] Vladimir Vapnik,et al. Statistical learning theory , 1998 .
[5] Xiaoli Zhang,et al. An ACO-based algorithm for parameter optimization of support vector machines , 2010, Expert Syst. Appl..
[6] 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..
[7] Heinz Mühlenbein,et al. The Equation for Response to Selection and Its Use for Prediction , 1997, Evolutionary Computation.
[8] Xin-She Yang,et al. Bat algorithm: a novel approach for global engineering optimization , 2012, 1211.6663.
[9] Shiliang Sun,et al. A review of optimization methodologies in support vector machines , 2011, Neurocomputing.
[10] Shigeo Abe. Support Vector Machines for Pattern Classification , 2010, Advances in Pattern Recognition.
[11] Dayou Liu,et al. Evolving support vector machines using fruit fly optimization for medical data classification , 2016, Knowl. Based Syst..
[12] Yunqiang Zhang,et al. Machine training and parameter settings with social emotional optimization algorithm for support vector machine , 2015, Pattern Recognit. Lett..
[13] Bernd Bischl,et al. Effectiveness of Random Search in SVM hyper-parameter tuning , 2015, 2015 International Joint Conference on Neural Networks (IJCNN).
[14] Martín Carpio,et al. Hyper-Parameter Tuning for Support Vector Machines by Estimation of Distribution Algorithms , 2017, Nature-Inspired Design of Hybrid Intelligent Systems.
[15] Asdrúbal López Chau,et al. Support vector machine classification for large datasets using decision tree and Fisher linear discriminant , 2014, Future Gener. Comput. Syst..
[16] Mu-Chen Chen,et al. Credit scoring with a data mining approach based on support vector machines , 2007, Expert Syst. Appl..
[17] Sayan Mukherjee,et al. Choosing Multiple Parameters for Support Vector Machines , 2002, Machine Learning.
[18] James Kennedy,et al. Particle swarm optimization , 2002, Proceedings of ICNN'95 - International Conference on Neural Networks.
[19] E. M. Wright,et al. Adaptive Control Processes: A Guided Tour , 1961, The Mathematical Gazette.
[20] Nello Cristianini,et al. Kernel Methods for Pattern Analysis , 2004 .
[21] Marti A. Hearst. Trends & Controversies: Support Vector Machines , 1998, IEEE Intell. Syst..
[22] Janez Brest,et al. A Brief Review of Nature-Inspired Algorithms for Optimization , 2013, ArXiv.
[23] Yoshua Bengio,et al. Random Search for Hyper-Parameter Optimization , 2012, J. Mach. Learn. Res..
[24] Aditi Goel,et al. Role of Kernel Parameters in Performance Evaluation of SVM , 2016, 2016 Second International Conference on Computational Intelligence & Communication Technology (CICT).
[25] Chih-Jen Lin,et al. LIBSVM: A library for support vector machines , 2011, TIST.
[26] Andreas Christmann,et al. Support vector machines , 2008, Data Mining and Knowledge Discovery Handbook.
[27] Zne-Jung Lee,et al. Parameter determination of support vector machine and feature selection using simulated annealing approach , 2008, Appl. Soft Comput..