Support vector machines on the space of Walsh functions and their properties
Attila Fazekas, Constantine L. Kotropoulos, Ioan Buciu, Ioannis Pitas · 2002
Support vector machine is a special kind of learning machine, proposed by Vapnik. The learning capability of support vector machines depends on the Vapnik-Chervonenkis (VC) dimension of the kernel function used. In this paper, we construct a new kernel function for support vector machine, which is based on Walsh functions. We prove some theoretical results related to the VC-dimension of the support vector machines which are built in the space of the Walsh functions. First experimental results for face detection are reported.