Abstract
The well-known MinOver algorithm is a simple modification of the perceptron algorithm and provides the maximum margin classifier without a bias in linearly separable two class classification problems. DoubleMinOver as a slight modification of MinOver is introduced, which now includes a bias. It is shown how this simple and iterative procedure can be extended to SoftDoubleMinOver for classification with soft margins and with kernels. On benchmarks the extremely simple SoftDoubleMinOver algorithm achieves the same classification performance with the same computational effort as sophisticated Support-Vector-Machine software.
An erratum to this chapter can be found at http://dx.doi.org/10.1007/11550907_163 .
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Martinetz, T., Labusch, K., Schneegaß, D. (2005). SoftDoubleMinOver: A Simple Procedure for Maximum Margin Classification. In: Duch, W., Kacprzyk, J., Oja, E., Zadrożny, S. (eds) Artificial Neural Networks: Formal Models and Their Applications – ICANN 2005. ICANN 2005. Lecture Notes in Computer Science, vol 3697. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11550907_48
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DOI: https://doi.org/10.1007/11550907_48
Publisher Name: Springer, Berlin, Heidelberg
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