¹Department of Mathematics, Shaoxing College of Arts and Sciences Shaoxing, Zhejiang 312000, China
²School of Mathematics and LPMC, Nankai University,Tianjin 300071, China

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Abstract—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 ) m and estimate the approximation error in terms of some kind of K -functional.

Index Terms—Least Square Regressions, Data Dependent Hypothesis, Coefficient Regularization, General Kernel, Learning Rate.

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Cite: Bao-Huai Sheng, Pei-Xin Ye, "Least Square Regression Learning with Data Dependent Hypothesis and Coefficient Regularzation," Journal of Computers vol. 6, no. 4, pp. 671-675, 2011.