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Neural Computation

September 1994, Vol. 6, No. 5, Pages 851-876
(doi: 10.1162/neco.1994.6.5.851)
© 1994 Massachusetts Institute of Technology
Measuring the VC-Dimension of a Learning Machine
Article PDF (908.58 KB)
Vladimir Vapnik
AT&T Bell Laboratories, Holmdel, NJ 07733 USA
Esther Levin
AT&T Bell Laboratories, Holmdel, NJ 07733 USA
Yann Le Cun
AT&T Bell Laboratories, Holmdel, NJ 07733 USA
Abstract

A method for measuring the capacity of learning machines is described. The method is based on fitting a theoretically derived function to empirical measurements of the maximal difference between the error rates on two separate data sets of varying sizes. Experimental measurements of the capacity of various types of linear classifiers are presented.