Complexity of families of learning algorithms and estimation of the nonrandomness of extraction of empirical regularities |
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Authors: | V I Donskoy |
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Affiliation: | 1. Taurida National V.I. Vernadskii University, Simferopol, Ukraine
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Abstract: | The paper presents a general approach to the evaluation of the complexity of classes of algorithms, so-called pVCD-method. To develop this method, all the examined families of models of empiric generalization were restricted to classes
implementable on computers and, wider, by examining their partially recursive representations. Within the framework of the
algorithmic approach, the concept of Kolmogorov’ complexity of algorithms for the recognition of properties or the extraction
of regularities is proposed. The method proposed to evaluate the nonrandomness of the extraction of empirical regularities
is based on this concept. |
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Keywords: | |
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