Applying Preference Biases to Conjunctive and Disjunctive Version Spaces

Authors:
Evgueni N. Smirnov;H. Jaap van den Herik
Affiliations:
-;-
Venue:
AIMSA '00 Proceedings of the 9th International Conference on Artificial Intelligence: Methodology, Systems, and Applications
Year:
2000

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Abstract

The paper considers conjunctive and disjunctive version space learning as an incomplete search in complete hypotheses spaces. The incomplete search is guided by preference biases which are implemented by procedures based on the instance-based boundary sets representation of version spaces. The conditions for tractability of this representation are defined. As a result we propose to use instance-based boundary sets as a basis for the computationally feasible application of preference biases to version spaces.