A new definition of neighborhood of a point in multi-dimensional space
Pattern Recognition Letters
Analysis of new techniques to obtain quality training sets
Pattern Recognition Letters - Special issue: Sibgrapi 2001
On Classifier Domains of Competence
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 1 - Volume 01
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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.