Notice of Violation of IEEE Publication PrinciplesAn explicit solution for generalized ridge regression

Notice of Violation of IEEE Publication Principles

"An Explicit Solution for Generalized Ridge Regression"
by Zhi-Fu Wang, Xian-Wei Yu, Xiao-Gang Liu, Liang-Kuan Zhu
in the 2003 Proceedings of the Second International Conference on Machine Learning
and Cybernetics, vol. 1, pp 485-489.

After careful and considered review of the content and authorship of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE\´s Publication Principles.

This paper is a near duplication of the original text from the paper cited below. The original text was copied without attribution (including appropriate references to the original author(s) and/or paper title) and without permission.

Due to the nature of this violation, reasonable effort should be made to remove all past references to this paper, and future references should be made to the following article:

" An Explicit Solution for Generalized Ridge Regression "
by William J. Hemmerle
in Technometrics, vol. 17, no. 3, American Statistical Association, August 1975, pp. 309-314The general form of ridge regression proposed by Hoerl and Kennard is examined in the content of the iterative procedure they suggest for obtaining optimal estimators. It is shown that a non-iterative, closed form solution is available for this procedure. The solution is found to depend upon certain convergence/divergence conditions that relate to the ordinary least squares estimators. Numerical examples are given.