A training algorithm for optimal margin classifiers
COLT '92 Proceedings of the fifth annual workshop on Computational learning theory
Evolutionary computation: toward a new philosophy of machine intelligence
Evolutionary computation: toward a new philosophy of machine intelligence
The nature of statistical learning theory
The nature of statistical learning theory
Machine Learning
An introduction to support Vector Machines: and other kernel-based learning methods
An introduction to support Vector Machines: and other kernel-based learning methods
Evolution and Optimum Seeking: The Sixth Generation
Evolution and Optimum Seeking: The Sixth Generation
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Learning and Soft Computing: Support Vector Machines, Neural Networks, and Fuzzy Logic Models
Learning and Soft Computing: Support Vector Machines, Neural Networks, and Fuzzy Logic Models
Evolution strategies –A comprehensive introduction
Natural Computing: an international journal
Adaptive integration using evolutionary strategies
HIPC '96 Proceedings of the Third International Conference on High-Performance Computing (HiPC '96)
ICDAR '01 Proceedings of the Sixth International Conference on Document Analysis and Recognition
Support Vector Machines: Training and Applications
Support Vector Machines: Training and Applications
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
Kernel Methods for Pattern Analysis
Kernel Methods for Pattern Analysis
Multi-objective model selection for support vector machines
EMO'05 Proceedings of the Third international conference on Evolutionary Multi-Criterion Optimization
An introduction to kernel-based learning algorithms
IEEE Transactions on Neural Networks
Evolving kernels for support vector machine classification
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Kernel Trees for Support Vector Machines
IEICE - Transactions on Information and Systems
A Family-Based Evolutional Approach for Kernel Tree Selection in SVMs
PAKDD '09 Proceedings of the 13th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining
Proceedings of the 11th Annual conference on Genetic and evolutionary computation
Evolutionary Optimization of Kernel Weights Improves Protein Complex Comembership Prediction
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
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In support vector machines (SVM), the kernel functions which compute dot product in feature space significantly affect the performance of classifiers. Each kernel function is suitable for some tasks. A universal kernel is not possible, and the kernel must be chosen for the tasks under consideration by hand. In order to obtain a flexible kernel function, a family of radial basis function (RBF) kernels is proposed. Multi-scale RBF kernels are combined by including weights. Then, the evolutionary strategies are used to adjust these weights and the widths of the RBF kernels. The proposed kernel is proved to be a Mercer's kernel. The experimental results show that the use of multi-scale RBF kernels result in better performance than that of a single Gaussian RBF on benchmarks.