Title :
Selection of classifiers based on the MDL principle using the VC dimension
Author :
Kudo, Mineichi ; Shimbo, Masm
Author_Institution :
Dept. of Inf. Eng., Hokkaido Univ., Sapporo, Japan
Abstract :
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
Keywords :
pattern classification; MDL principle; VC dimension; Vapnick-Chervonenkis dimension; classifier selection; combinational property; minimum description length criterion; pattern recognition problem; Communication channels; Costs; Decision trees; Decoding; Length measurement; Pattern recognition; Silicon carbide; Tin; Virtual colonoscopy;
Conference_Titel :
Pattern Recognition, 1996., Proceedings of the 13th International Conference on
Conference_Location :
Vienna
Print_ISBN :
0-8186-7282-X
DOI :
10.1109/ICPR.1996.547203
