Generating classifier outputs of fixed accuracy and diversity

Authors:
Ludmila I. Kuncheva;Roumen K. Kountchev
Affiliations:
School of Informatics, University of Wales Bangor, Dean Street, Bangor, Gwynedd, UK;School of Informatics, University of Wales Bangor, Dean Street, Bangor, Gwynedd, UK
Venue:
Pattern Recognition Letters
Year:
2002

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Abstract

We offer an algorithm for random generation of classifier outputs with specified individual accuracies and pairwise dependencies. The outputs are binary vectors (correct/incorrect classification) for a hypothetical data set. The generated team output can be used to study the majority vote over multiple dependent classifiers.