On domain knowledge and feature selection using a support vector machine
نویسندگان
چکیده
The basic principles of a support vector machine (SVM) are analyzed. The problem of feature selection while using an SVM is speci®cally addressed. An approach to constructing a kernel function which takes into account some domain knowledge about a problem and thus essentially diminishes the number of noisy parameters in high dimensional feature space is suggested. Its application to Texture Recognition is described. Ó 1999 Elsevier Science B.V. All rights reserved.
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عنوان ژورنال:
- Pattern Recognition Letters
دوره 20 شماره
صفحات -
تاریخ انتشار 1999