Abstract
This paper addresses the problem of dynamic configuration of multiclassifier systems. For this purpose, the performance of combination methods for abstract-level classifiers is predicted, under different working conditions, and sets of rules are discovered and used for dynamic configuration of multiclassifier systems. The experimental tests have been carried out in the field of hand-written numeral recognition. The result demonstrates the validity of the proposed approach.
Cite
CITATION STYLE
Dimauro, G., Impedovo, S., Lucchese, M. G., Pirlo, G., & Salzo, A. (2002). Discovering rules for dynamic configuration of multi-classifier systems. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2423, pp. 157–166). Springer Verlag. https://doi.org/10.1007/3-540-45869-7_20
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