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1. L. Micó; F. Moreno-Seco; J. S. Sánchez; J. M. Sotoca; R. A. Mollineda
   "On the use of different classification rules in an editing task"
   Lecture Notes in Computer Science, vol. 4109, pp. 747--754 (2006)
   : bibtex : pdf
   Abstract:

   Editing allows the selection of a representative subset of prototypes among the training sample to improve the performance of a classification task. The Wilson's editing algorithm was the first proposal and then a great variety of new editing techniques have been proposed based on it. This algorithm consists on the elimination of prototypes in the training set that are misclassified using the k-NN rule. From such editing scheme, a general editing procedure can be straightforward derived, where any classifier beyond k-NN can be used. In this paper, we analyze the behavior of this general editing procedure combined with 3 different neighborhood-based classification rules, including k-NN. The results reveal better performances of the 2 other techniques with respect to k-NN in most of cases.

@article {
 author = "L. Micó; F. Moreno-Seco; J. S. Sánchez; J. M. Sotoca; R. A. Mollineda",
 title  = "On the use of different classification rules in an editing task",
 journal = "Lecture Notes in Computer Science",
 pages = "747--754",
 volume = "4109",
 year = "2006"
}