Abstract
We propose a method for the random generation of classifier outputs with specified individual accuracies and fixed pairwise agreement. A diversity measure (kappa) is used to control the agreement among classifiers for building the classifier teams. The generated team outputs can be used to study the behaviour of class-type combination methods such as voting rules over multiple dependent classifiers.
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© 2005 Springer-Verlag Berlin Heidelberg
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Zouari, H., Heutte, L., Lecourtier, Y. (2005). Using Diversity Measure in Building Classifier Ensembles for Combination Method Analysis. In: Kurzyński, M., Puchała, E., Woźniak, M., żołnierek, A. (eds) Computer Recognition Systems. Advances in Soft Computing, vol 30. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-32390-2_39
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DOI: https://doi.org/10.1007/3-540-32390-2_39
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