7-5 “Hold out! NTSC”

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Efficient Hold-Out for Subset of Regressors

Hold-out and cross-validation are among the most useful methods for model selection and performance assessment of machine learning algorithms. In this paper, we present a computationally efficient algorithm for calculating the hold-out performance for sparse regularized least-squares (RLS) in case the method is already trained with the whole training set. The computational complexity of perform...

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ژورنال

عنوان ژورنال: The Journal of the Institute of Television Engineers of Japan

سال: 1989

ISSN: 0386-6831,1884-9652

DOI: 10.3169/itej1978.43.404