Variogram based noise variance estimation and its use in kernel based regression

نویسندگان

  • Kristiaan Pelckmans
  • Jos De Brabanter
  • Johan A. K. Suykens
  • Bart De Moor
چکیده

Model-free estimates of the noise variance are important for doing model selection and setting tuning parameters. In this paper a data representation is discussed which leads to such an estimator suitable for multidimensional input data. The visual representation called the differogram cloud is based on the 2-norm of the differences of the inputand output-data. A corrected way to estimate the variance of the noise on the output measurement and a (tuning-) parameter free version are derived. Connections with other existing variance estimators and numerical simulations indicate convergence of the estimators. As a special case, this paper focuses on model selection and tuning parameters of Least Squares Support Vector Machines [19].

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تاریخ انتشار 2003