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The one-inclusion graph algorithm is near-optimal for the prediction model of learning

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3 Author(s)
Yi Li ; Dept. of Comput. Sci., Nat. Univ. of Singapore, Singapore ; Long, P.M. ; Srinivasan, A.

Haussler, Littlestone and Warmuth (1994) described a general-purpose algorithm for learning according to the prediction model, and proved an upper bound on the probability that their algorithm makes a mistake in terms of the number of examples seen and the Vapnik-Chervonenkis (VC) dimension of the concept class being learned. We show that their bound is within a factor of 1+o(1) of the best possible such bound for any algorithm

Published in:

Information Theory, IEEE Transactions on  (Volume:47 ,  Issue: 3 )

Date of Publication:

Mar 2001

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