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An efficient data structure for decision rules discovery

Opened Access An efficient data structure for decision rules discovery


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Autor: Giráldez Rojo, Raúl
Aguilar Ruiz, Jesús Salvador
Riquelme Santos, José Cristóbal
Departamento: Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos
Fecha: 2003
Publicado en: SAC '03 Proceedings of the 2003 ACM symposium on Applied computing, pp. 475-479 (2003)
Tipo de documento: Capítulo de Libro
Resumen: The increasing amount of information available is encouraging the search for efficient techniques to improve the data mining methods, especially those which consume great computational resources. We present a novel structure, called EES, which helps the data mining algorithms which generate decision rules to reduce the aforementioned cost. Given that decision rules establish conditions for database attributes, EES stores the information in such a way that the search can be carried out by attributes instead of by examples. EES could be useful for any method which generates decision rules. Moreover, it is of particular interest when the search for the solution involves a great many hypothetical solutions. Thus, this structure is designed for speeding up the rule-evaluation process in methods based on Evolutionary Algorithms. The traditional structure, based on vectors of examples (in which the database is stored) is evaluated and compared with EES, including the costs for a stratified s...
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