Selection of classifiers based on the MDL principle using the VC dimension
Mineichi Kudo, Masaru Shimbo · 1996
The MDL (minimum description length) criterion is used to select the best classifier among several types of classifiers on a given pattern recognition problem. Unlike previous studies, our technique can compare a wide variety of classifiers if we know a combinational property, viz., the Vapnick-Chervonenkis (VC) dimension. Three classifiers are compared using this criterion. Experimental results show the effectiveness of the method.