Journal of Econometrics is on level 4 in the ABS Academic Journal Guide.

Otneim, Håkon, Martin Jullum and Dag Tjøstheim: Pairwise local Fisher and naive Bayes: Improving two standard discriminants, Journal of Econometrics, Online 01.02.2020.

Abstract

The Fisher discriminant is probably the best known likelihood discriminant for continuous data. Another benchmark discriminant is the naive Bayes, which is based on marginals only. In this paper we extend both discriminants by modeling dependence between pairs of variables. In the continuous case this is done by local Gaussian versions of the Fisher discriminant.

In the discrete case the naive Bayes is extended by taking geometric averages of pairwise joint probabilities. We also indicate how the two approaches can be combined for mixed continuous and discrete data. The new discriminants show promising results in a number of simulation experiments and real data illustrations.

• Share on Facebook
• Share on Twitter
• Share on LinkedIn
• Share by e-mail