This page is devoted to show the supplementary materials for the paper entitled "PBC4occ: A novel contrast pattern-based classifier for one-class classification" published in Future Generation Computer Systems, July 2021.

Classification results obtained by all the tested classifiers
  • AUC results ->
  • EER results ->

Statistical Tests

Statistical results using Friedman's test (as a non-parametric test) and Finner's procedure (as a post-hoc procedure) [1]. The post hoc comparisons contain α = 0.05, α = 0.10, and adjusted p-values.

  • Statistical results, according to both AUC and EER measures -> Download

PBC4occ Implementation

We have implemented the PBC4occ algorithm as a Weka Package. You can download this version from here ->


[1] J. Derrac, S. García, D. Molina, and F. Herrera, “A practical tutorial on the use of nonparametric statistical tests as a methodology for comparing evolutionary and swarm intelligence algorithms,” Swarm Evol. Comput., vol. 1, no. 1, pp. 3–18, 2011.