info:eu-repo/semantics/article
Classification based on specific rules and inexact coverage
Autor
RAUDEL HERNANDEZ LEON
Jesús Ariel Carrasco Ochoa
José Francisco Martínez Trinidad
Resumen
Association rule mining and classification are important tasks in data mining. Using association rules has proved to be a good approach for classification. In this paper, we propose an accurate classifier based on class association rules (CARs), called CAR-IC, which introduces a new pruning strategy for mining CARs, which allows building specific rules with high confidence. Moreover, we propose and prove three propositions that support the use of a confidence threshold for computing rules that avoids ambiguity at the classification stage. This paper also presents a new way for ordering the set of CARs based on rule size and confidence. Finally, we define a new coverage strategy, which reduces the number of non-covered unseen-transactions during the classification stage. Results over several datasets show that CAR-IC beats the best classifiers based on CARs reported in the literature.
Materias
Ítems relacionados
Mostrando ítems relacionados por Título, autor o materia.
-
Compendio de innovaciones socioambientales en la frontera sur de México
Adriana Quiroga -
Caminar el cafetal: perspectivas socioambientales del café y su gente
Eduardo Bello Baltazar; Lorena Soto_Pinto; Graciela Huerta_Palacios; Jaime Gomez -
Material de empaque para biofiltración con base en poliuretano modificado con almidón, metodos para la manufactura del mismo y sistema de biofiltración
OLGA BRIGIDA GUTIERREZ ACOSTA; VLADIMIR ALONSO ESCOBAR BARRIOS; SONIA LORENA ARRIAGA GARCIA