@misc{10481/77892,
year = {2006},
url = {https://hdl.handle.net/10481/77892},
abstract = {Separate-and-conquer classifiers strongly depend on the criteria
used to choose which rules will be included in the classification
model. When association rules are employed to build such classifiers (as
in ART [3]), rule evaluation can be performed attending to different criteria
(other than the traditional confidence measure used in association
rule mining). In this paper, we analyze the desirable properties of such
alternative criteria and their effect in building rule-based classifiers using
a separate-and-conquer strategy.},
publisher = {Springer},
keywords = {Inteligencia artificial},
keywords = {Artificial intelligence},
title = {An Overview of Alternative Rule Evaluation Criteria and Their Use in Separate-and-Conquer Classifiers},
author = {Berzal Galiano, Fernando and Cubero Talavera, Juan Carlos and Marín Ruiz, Nicolás and Polo, José Luis},
}