An introduction to support Vector Machines: and other kernel-based learning methods
An introduction to support Vector Machines: and other kernel-based learning methods
Advances in Large Margin Classifiers
Advances in Large Margin Classifiers
SVMTorch: support vector machines for large-scale regression problems
The Journal of Machine Learning Research
A comparison of methods for multiclass support vector machines
IEEE Transactions on Neural Networks
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In this paper we introduce a new family of hyperplane classifiers. But, in contrast to Support Vector Machines (SVM) - where a constrained quadratic optimization is used - some of the proposed methods lead to the unconstrained minimization of convex functions while others merely require solving a linear System of equations. So that the efficiency of these methods could be checked, classification tests were conducted on standard databases. In our evaluation, classification results of SVM were of course used as a general point of reference, which we found were outperformed in many cases.