On the minimum probability of classification error through effective cardinality comparison

Authors

  • Jugurta Montalvão Federal University of Sergipe
  • Jânio Canuto Federal University of Sergipe
  • Elyson Carvalho Federal University of Sergipe

DOI:

https://doi.org/10.14209/jcis.2016.26

Keywords:

Entropy through coincidence, Multivariate statistics, Collision entropy, Effective cardinality, Classification error probability.

Abstract

A straightforward ''collision'' (quadratic) entropy estimator is used to give support, in a very pragmatic approach, to data analysis based on the concept of effective cardinality of sets. Thus, by using basic concepts of probability and set theories, a method is proposed to estimate the minimum probability of classification error, in two-class problems, without the deployment of any particular classifier. The usefulness as well as some limitations of the analysis based on effective cardinality are exemplified throughout the text.

Downloads

Download data is not yet available.

Downloads

Published

2016-11-03

How to Cite

Montalvão, J., Canuto, J., & Carvalho, E. (2016). On the minimum probability of classification error through effective cardinality comparison. Journal of Communication and Information Systems, 31(1). https://doi.org/10.14209/jcis.2016.26

Issue

Vol. 31 No. 1 (2016)

Section

Regular Papers

License

Authors who publish in this journal agree to the following terms:

  1. Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a CC BY-NC 4.0 (Attribution-NonCommercial 4.0 International) that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
  2. Authors can enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
  3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) before and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).

___________

Received 2016-07-11
Accepted 2016-10-26
Published 2016-11-03

Most read articles by the same author(s)