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New Criterion for Choosing the Number of Parameters in a RKHS Model


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DOI: https://doi.org/10.15866/ireaco.v7i6.2931

Abstract


This paper proposes a new algorithm to estimate the required number of parameters in the models developed in Reproducing Kernel Hilbert Space (RKHS). The proposed method considers models with growing complexities and calculates for each a given matrix, such that these matrices tend to singularity. The required number of parameters is given by verifying a criterion on the determinants of these matrices.
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Keywords


Determinant Ratio; RKHS; RKPCA

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References


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