Abstract
Two extensions of the original Wilson’s editing method are introduced in this paper. These new algorithms are based on estimating probabilities from the k-nearest neighbor patterns of an instance, in order to obtain more compact edited sets while maintaining the classification rate. Several experiments with synthetic and real data sets are carried out to illustrate the behavior of the algorithms proposed here and compare their performance with that of other traditional techniques.
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© 2005 Springer-Verlag Berlin Heidelberg
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Vázquez, F., Sánchez, J.S., Pla, F. (2005). A Stochastic Approach to Wilson’s Editing Algorithm. In: Marques, J.S., Pérez de la Blanca, N., Pina, P. (eds) Pattern Recognition and Image Analysis. IbPRIA 2005. Lecture Notes in Computer Science, vol 3523. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11492542_5
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DOI: https://doi.org/10.1007/11492542_5
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-26154-4
Online ISBN: 978-3-540-32238-2
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