From satisfiability to consistency through certificates: application to partially defined constraints

Authors:
Arnaud Lallouet;Andrei Legtchenko
Affiliations:
Universite d'Orleans, BP, Orleans Cedex;Universite d'Orleans, BP, Orleans Cedex
Venue:
Proceedings of the 2006 ACM symposium on Applied computing
Year:
2006

Citing 5
Cited 0

C4.5: programs for machine learning

C4.5: programs for machine learning
The essence of constraint propagation

Theoretical Computer Science
Interval arithmetic: From principles to implementation

Journal of the ACM (JACM)
Machine Learning

Machine Learning
Two contributions of constraint programming to machine learning

ECML'05 Proceedings of the 16th European conference on Machine Learning

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper, we propose a method to automatically derive a filtering algorithm from a constraint expressed by its satisfiability function. We give an application of the technique in the field of Machine Learning in which partially defined constraints are learned by decision trees.