Abstract
In a discussion of the Vapnik Chervonenkis (VC) dimension ([7]), which is closely related to the learnability of concept classes in Valiant's PAC-model ([6]), we will give an algorithm to compute it. Furthermore, we will take Natarajan's equivalent dimension for well-ordered classes into a more general scheme, by showing that these well-ordered classes happen to satisfy some general condition, which makes it possible to construct for a class a number of equivalent dimensions. We will give this condition, as well as a relatively efficient algorithm for the calculation of one such dimension for well-ordered classes.
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© 1993 Springer-Verlag Berlin Heidelberg
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Nienhuys-Cheng, S.H., Polman, M. (1993). Complexity dimensions and learnability. In: Brazdil, P.B. (eds) Machine Learning: ECML-93. ECML 1993. Lecture Notes in Computer Science, vol 667. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-56602-3_149
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DOI: https://doi.org/10.1007/3-540-56602-3_149
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