CAR-NF + : An Improved Version of CAR-NF Classifier

  • Raudel Hernández-León
  • José Hernández-Palancar
  • Jesús Ariel Carrasco-Ochoa
  • José Francisco Martínez-Trinidad
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7441)

Abstract

In this paper, we propose two improvements to CAR-NF classifier, which is a classifier based on Class Association Rules (CARs). The first one, is a theoretical proof that allows selecting the minimum Netconf threshold, independently of the dataset, that avoids ambiguity at the classification stage. The second one, is a new coverage criterion, which aims to reduce the number of non-covered unseen-transactions during the classification stage. Experiments over several datasets show that the improved classifier, called CAR-NF + , beats the best reported classifiers based on CARs, including the original CAR-NF classifier.

Keywords

Data mining Supervised classification Class association rules 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Raudel Hernández-León
    • 1
  • José Hernández-Palancar
    • 1
  • Jesús Ariel Carrasco-Ochoa
    • 2
  • José Francisco Martínez-Trinidad
    • 2
  1. 1.Centro de Aplicaciones de Tecnologías de Avanzada (CENATAV)La HabanaCuba
  2. 2.Computer Science DepartmentInstituto Nacional de Astrofísica, Óptica y Electrónica (INAOE)PueblaMéxico

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