%0 Journal Article
%T Least Square Regression Learning with Data Dependent Hypothesis and Coefficient Regularzation
%A Baohuai Sheng
%A Pei-Xin Ye
%J Journal of Computers
%D 2011
%I Academy Publisher
%R 10.4304/jcp.6.4.671-675
%X We study the least square regression with data dependent hypothesis and coefficient regularization algorithms based on general kernel. An explicit expression of the solution of this kernel scheme is derived. Then we provide a sample error with a decay of <o(1/sqr(m)) and estimate the approxi -mation error in terms of some kind of K-functional.
%K Least Square Regressions
%K Data Depen -dent Hypothesis
%K Coefficient Regulari -zation
%K General Kernel
%K Learning Rate.
%U http://ojs.academypublisher.com/index.php/jcp/article/view/3860