کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
531312 | 869827 | 2009 | 7 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: Model selection for the LS-SVM. Application to handwriting recognition Model selection for the LS-SVM. Application to handwriting recognition](/preview/png/531312.png)
The support vector machine (SVM) is a powerful classifier which has been used successfully in many pattern recognition problems. It has also been shown to perform well in the handwriting recognition field. The least squares SVM (LS-SVM), like the SVM, is based on the margin-maximization principle performing structural risk minimization. However, it is easier to train than the SVM, as it requires only the solution to a convex linear problem, and not a quadratic problem as in the SVM. In this paper, we propose to conduct model selection for the LS-SVM using an empirical error criterion. Experiments on handwritten character recognition show the usefulness of this classifier and demonstrate that model selection improves the generalization performance of the LS-SVM.
Journal: Pattern Recognition - Volume 42, Issue 12, December 2009, Pages 3264–3270