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Alternative method for choosing ridge parameter for regression
Ridge regression Ridge parameter Multicollinearity
2010/9/20
The parameter estimation method based on minimum residual sum of squares is unsatisfactory in the presence of multicollinearity. Hoerl and Kennard [1] introduced alternative method called ridge regres...
A Monte Carlo comparison between ridge and principal components regression methods
Multicollinearity ridge regression principal component regression
2010/9/15
A basic assumption concerned with general linear regression model is that there is no correlation (or no multicollinearity) between the explanatory variables. When this assumption is not satisfied, th...
Universal Approximation by Ridge Computational Models and Neural Networks: A Survey
nonlinear computational models ridge computational units universal approximation com-plexity
2008/11/10
Computational models made up of linear combinations of ridge basis functions, widely used in machine learning and artificial intelligence, are considered. For such models, the literature on the so-cal...
Computational Mathematics Group at Oak Ridge National Laboratory
numerical algorithms computational mathematics
2007/12/25
The Computational Mathematics Group is devoted to the development, analysis and application of efficient numerical algorithms for solving large-scale scientific and engineering problems on advanced co...