The nature of statistical learning theory
The nature of statistical learning theory
Making large-scale support vector machine learning practical
Advances in kernel methods
“Genotypes” for neural networks
The handbook of brain theory and neural networks
An introduction to support Vector Machines: and other kernel-based learning methods
An introduction to support Vector Machines: and other kernel-based learning methods
Machine Learning
Theory of evolution strategies - a tutorial
Theoretical aspects of evolutionary computing
Evolution and Optimum Seeking: The Sixth Generation
Evolution and Optimum Seeking: The Sixth Generation
Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond
Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond
Evolution strategies –A comprehensive introduction
Natural Computing: an international journal
Choosing Multiple Parameters for Support Vector Machines
Machine Learning
Radius margin bounds for support vector machines with the RBF kernel
Neural Computation
Feature Selection for Support Vector Machines by Means of Genetic Algorithms
ICTAI '03 Proceedings of the 15th IEEE International Conference on Tools with Artificial Intelligence
Completely Derandomized Self-Adaptation in Evolution Strategies
Evolutionary Computation
Analysis of a simple evolutionary algorithm for minimization in euclidean spaces
ICALP'03 Proceedings of the 30th international conference on Automata, languages and programming
Efficient tuning of SVM hyperparameters using radius/margin bound and iterative algorithms
IEEE Transactions on Neural Networks
Gradient-Based Adaptation of General Gaussian Kernels
Neural Computation
Neural Networks - Special issue on neural networks and kernel methods for structured domains
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Evolving kernels for support vector machine classification
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Artificial Intelligence in Medicine
Journal of Biomedical Informatics
Uncertainty Handling in Model Selection for Support Vector Machines
Proceedings of the 10th international conference on Parallel Problem Solving from Nature: PPSN X
SVM-based segmentation and classification of remotely sensed data
International Journal of Remote Sensing
Associated evolution of a support vector machine-based classifier for pedestrian detection
Information Sciences: an International Journal
Kernel Trees for Support Vector Machines
IEICE - Transactions on Information and Systems
A Learning Algorithm of Boosting Kernel Discriminant Analysis for Pattern Recognition
IEICE - Transactions on Information and Systems
Expert Systems with Applications: An International Journal
Learning by local kernel polarization
Neurocomputing
Expert Systems with Applications: An International Journal
A novel SVR parameter selection base on bi-level programming problem
CCDC'09 Proceedings of the 21st annual international conference on Chinese control and decision conference
Evolutionary Model Type Selection for Global Surrogate Modeling
The Journal of Machine Learning Research
Simultaneous tuning of hyperparameter and parameter for support vector machines
PAKDD'07 Proceedings of the 11th Pacific-Asia conference on Advances in knowledge discovery and data mining
Experiments on kernel tree support vector machines for text categorization
PAKDD'07 Proceedings of the 11th Pacific-Asia conference on Advances in knowledge discovery and data mining
Evolutionary feature and parameter selection in support vector regression
MICAI'07 Proceedings of the artificial intelligence 6th Mexican international conference on Advances in artificial intelligence
MP-polynomial kernel for training support vector machines
CIARP'07 Proceedings of the Congress on pattern recognition 12th Iberoamerican conference on Progress in pattern recognition, image analysis and applications
Optimising multiple kernels for SVM by genetic programming
EvoCOP'08 Proceedings of the 8th European conference on Evolutionary computation in combinatorial optimization
IITA'09 Proceedings of the 3rd international conference on Intelligent information technology application
An ACO-based algorithm for parameter optimization of support vector machines
Expert Systems with Applications: An International Journal
Feature selection for SVM via optimization of kernel polarization with Gaussian ARD kernels
Expert Systems with Applications: An International Journal
Fundamenta Informaticae - Intelligent Data Analysis in Granular Computing
Stochastic feature selection in support vector machine based instrument recognition
KI'09 Proceedings of the 32nd annual German conference on Advances in artificial intelligence
Computers in Biology and Medicine
Short term wind speed prediction based on evolutionary support vector regression algorithms
Expert Systems with Applications: An International Journal
An optimal method for prediction and adjustment on byproduct gas holder in steel industry
Expert Systems with Applications: An International Journal
Model selection for least squares support vector regressions based on small-world strategy
Expert Systems with Applications: An International Journal
Multi-objective uniform design as a SVM model selection tool for face recognition
Expert Systems with Applications: An International Journal
Evolution strategies based adaptive Lp LS-SVM
Information Sciences: an International Journal
Extended Bayesian framework for automatic tuning of kernel data-mining methods
ACS'06 Proceedings of the 6th WSEAS international conference on Applied computer science
Tuning metaheuristics: A data mining based approach for particle swarm optimization
Expert Systems with Applications: An International Journal
Genetic programming for kernel-based learning with co-evolving subsets selection
PPSN'06 Proceedings of the 9th international conference on Parallel Problem Solving from Nature
PSO-Based hyper-parameters selection for LS-SVM classifiers
ICONIP'06 Proceedings of the 13th international conference on Neural Information Processing - Volume Part II
Evolutionary optimization of sequence kernels for detection of bacterial gene starts
ICANN'06 Proceedings of the 16th international conference on Artificial Neural Networks - Volume Part II
Swarm intelligent tuning of one-class v-SVM parameters
RSKT'06 Proceedings of the First international conference on Rough Sets and Knowledge Technology
Expert Systems with Applications: An International Journal
Statistical processes monitoring based on improved ICA and SVDD
ICIC'06 Proceedings of the 2006 international conference on Intelligent Computing - Volume Part I
The use of stability principle for kernel determination in relevance vector machines
ICONIP'06 Proceedings of the 13 international conference on Neural Information Processing - Volume Part I
Expert Systems with Applications: An International Journal
ICCSA'12 Proceedings of the 12th international conference on Computational Science and Its Applications - Volume Part III
Automatic surrogate model type selection during the optimization of expensive black-box problems
Proceedings of the Winter Simulation Conference
An efficient multiple-kernel learning for pattern classification
Expert Systems with Applications: An International Journal
Evolutionary computation for supervised learning
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
A nested heuristic for parameter tuning in Support Vector Machines
Computers and Operations Research
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The problem of model selection for support vector machines (SVMs) is considered. We propose an evolutionary approach to determine multiple SVM hyperparameters: The covariance matrix adaptation evolution strategy (CMA-ES) is used to determine the kernel from a parameterized kernel space and to control the regularization. Our method is applicable to optimize non-differentiable kernel functions and arbitrary model selection criteria. We demonstrate on benchmark datasets that the CMA-ES improves the results achieved by grid search already when applied to few hyperparameters. Further, we show that the CMA-ES is able to handle much more kernel parameters compared to grid-search and that tuning of the scaling and the rotation of Gaussian kernels can lead to better results in comparison to standard Gaussian kernels with a single bandwidth parameter. In particular, more flexibility of the kernel can reduce the number of support vectors.