Back to Search Start Over

The VC-Dimension of Subclasses of Pattern Languages.

Authors :
Goos, G.
Hartmanis, J.
van Leeuwen, J.
Carbonell, Jaime G.
Siekmann, Jörg
Watanabe, Osamu
Yokomori, Takashi
Carbonell, J. G.
Siekmann, J.
Mitchell, Andrew
Scheffer, Tobias
Sharma, Arun
Stephan, Frank
Source :
Algorithmic Learning Theory (9783540667483); 1999, p93-105, 13p
Publication Year :
1999

Abstract

This paper derives the Vapnik Chervonenkis dimension of several natural subclasses of pattern languages. For classes with unbounded VC-dimension, an attempt is made to quantify the "rate of growth" of VC-dimension for these classes. This is achieved by computing, for each n, size of the "smallest" witness set of n elements that is shattered by the class. The paper considers both erasing (empty substitutions allowed) and nonerasing (empty substitutions not allowed) pattern languages. For erasing pattern languages, optimal bounds for this size — within polynomial order — are derived for the case of 1 variable occurrence and unary alphabet, for the case where the number of variable occurrences is bounded by a constant, and the general case of all pattern languages. The extent to which these results hold for nonerasing pattern languages is also investigated. Some results that shed light on efficient learning of subclasses of pattern languages are also given. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISBNs :
9783540667483
Database :
Supplemental Index
Journal :
Algorithmic Learning Theory (9783540667483)
Publication Type :
Book
Accession number :
33100474
Full Text :
https://doi.org/10.1007/3-540-46769-6_8