Choosing Multiple Parameters for Support Vector Machines
Machine Learning
Lexicographic Parsimony Pressure
GECCO '02 Proceedings of the Genetic and Evolutionary Computation Conference
Kernel Methods for Pattern Analysis
Kernel Methods for Pattern Analysis
Evolutionary strategies for multi-scale radial basis function kernels in support vector machines
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
The Genetic Kernel Support Vector Machine: Description and Evaluation
Artificial Intelligence Review
Neural Computation
Evolutionary learning with kernels: a generic solution for large margin problems
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Multiclass SVM Model Selection Using Particle Swarm Optimization
HIS '06 Proceedings of the Sixth International Conference on Hybrid Intelligent Systems
Credit scoring with a data mining approach based on support vector machines
Expert Systems with Applications: An International Journal
Strongly typed genetic programming
Evolutionary Computation
Evolutionary tuning of multiple SVM parameters
Neurocomputing
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
Efficient tuning of SVM hyperparameters using radius/margin bound and iterative algorithms
IEEE Transactions on Neural Networks
A generic multi-dimensional feature extraction method using multiobjective genetic programming
Evolutionary Computation
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
Creation of Specific-to-Problem Kernel Functions for Function Approximation
IWANN '09 Proceedings of the 10th International Work-Conference on Artificial Neural Networks: Part I: Bio-Inspired Systems: Computational and Ambient Intelligence
Combined Unsupervised-Supervised Classification Method
KES '09 Proceedings of the 13th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems: Part II
A survey on the application of genetic programming to classification
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Evolving fisher kernels for biological sequence classification
Evolutionary Computation
Evolutionary computation for supervised learning
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
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While support vector machines (SVMs) have shown great promise in supervised classification problems, researchers have had to rely on expert domain knowledge when choosing the SVM's kernel function. This project seeks to replace this expert with a genetic programming (GP) system. Using strongly typed genetic programming and principled kernel closure properties, we introduce a new algorithm, called KGP, which finds near-optimal kernels. The algorithm shows wide applicability, but the combined computational overhead of GP and SVMs remains a major unresolved issue.