An introduction to genetic algorithms
An introduction to genetic algorithms
Pairwise classification and support vector machines
Advances in kernel methods
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
Reducing Multiclass to Binary: A Unifying Approach for Margin Classifiers
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
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
In Defense of One-Vs-All Classification
The Journal of Machine Learning Research
Solving multiclass learning problems via error-correcting output codes
Journal of Artificial Intelligence Research
LIBSVM: A library for support vector machines
ACM Transactions on Intelligent Systems and Technology (TIST)
New results on error correcting output codes of kernel machines
IEEE Transactions on Neural Networks
A review on the combination of binary classifiers in multiclass problems
Artificial Intelligence Review
IITA'09 Proceedings of the 3rd international conference on Intelligent information technology application
A genetic inspired optimization for ECOC
SSPR'12/SPR'12 Proceedings of the 2012 Joint IAPR international conference on Structural, Syntactic, and Statistical Pattern Recognition
On the design of an ECOC-Compliant Genetic Algorithm
Pattern Recognition
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Support Vector Machines constitute a Machine Learning technique originally designed for the solution of 2-class problems. For multiclass applications, several strategies divide the original problem into a set of binary subtasks, whose results are combined. This work introduces the use of Genetic Algorithms to determine binary decompositions of multiclass problems. Experimental results on benchmark and Bioinformatics multiclass datasets indicate the potential of the proposed approach, which is able to produce good multiclass solutions with the use of simple decompositions.