The Azimuth Project
Hierarchy of Classifiers

Andrius Kulikauskas, 2020.04.06: I have set up this page to organize thoughts on understanding Šarūnas Raudys’s hierarchy of classifiers. See this related Discussion on information theory.

Šarūnas Raudys describes the following hierarchy of classifiers:

  • the Euclidean distance classifier;
  • the standard Fisher linear discriminant function (DF);
  • the Fisher linear DF with pseudo-inversion of the covariance matrix;
  • regularized linear discriminant analysis;
  • the generalized Fisher DF;
  • the minimum empirical error classifier;
  • the maximum margin classifier.

Andrius Kulikauskas: My thought was that these classifiers might be distinguished by an increasing number of perspectives, from one to seven.