title: Generalization performance of Gaussian kernels SVMC based on Markov sampling.
abstract: In this paper we consider Gaussian RBF kernels support vector machine classification (SVMC) algorithm with uniformly ergodic Markov chain (u.e.M.c.) samples in reproducing kernel Hilbert spaces (RKHS). We analyze the learning rates of Gaussian RBF kernels SVMC based on u.e.M.c. samples and obtain the fast learning rate of Gaussian RBF kernels SVMC based on u.e.M.c. samples by using the strongly mixing property of u.e.M.c. samples. We also present the numerical studies on the learning performance of Gaussian RBF kernels SVMC based on Markov sampling for real-world datasets. These experimental results show that Gaussian RBF kernels SVMC based on Markov sampling has better learning performance compared to randomly independent sampling.
authors: Faculty of Mathematics and Computer Science, Hubei University, Wuhan 430062, China. Electronic address: jiexu@mail.hust.edu.cn.
authors: Jie
authors: J
authors: Xu
authors: Faculty of Science and Technology, University of Macau, China. Electronic address: yytang@umac.mo.
authors: Yuan Yan
authors: YY
authors: Tang
authors: Faculty of Mathematics and Computer Science, Hubei University, Wuhan 430062, China. Electronic address: zoubin0502@gmail.com.
authors: Bin
authors: B
authors: Zou
authors: Institute for Information and System Science, Xi'an Jiaotong University, Xi'an 710049, China. Electronic address: zbxu@mail.xjtu.edu.cn.
authors: Zongben
authors: Z
authors: Xu
authors: Faculty of Mathematics and Computer Science, Hubei University, Wuhan 430062, China. Electronic address: humcli@gmail.com.
authors: Luoqing
authors: L
authors: Li
authors: Faculty of Science and Technology, University of Macau, China. Electronic address: lylylytc@gmail.com.
authors: Yang
authors: Y
authors: Lu
mesh_terms: D008390:Markov Chains; D016571:Neural Networks, Computer; D060388:Support Vector Machine
keywords: Gaussian RBF kernels; Generalization performance; Markov sampling; SVMC; Uniformly ergodic Markov chain (u.e.M.c.)