Abstract
This paper presents a method of combining SVMs (support vector machines) for multiclass problems that ensures a high recognition rate and a short processing time when compared to other classifiers. This hierarchical SVM combination considers the high recognition rate and short processing time as evaluation criteria. The used case study was the handwritten digit recognition problem with promising results.
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Neves, R.F.P., Zanchettin, C., Filho, A.N.G.L. (2012). An Efficient Way of Combining SVMs for Handwritten Digit Recognition. In: Villa, A.E.P., Duch, W., Érdi, P., Masulli, F., Palm, G. (eds) Artificial Neural Networks and Machine Learning – ICANN 2012. ICANN 2012. Lecture Notes in Computer Science, vol 7553. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33266-1_29
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DOI: https://doi.org/10.1007/978-3-642-33266-1_29
Publisher Name: Springer, Berlin, Heidelberg
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