| Autor: |
Dit-Yan Yeung, Kwok, James T., Fred, Ana, Roli, Fabio, de Ridder, Dick, Micó, Luisa, Moreno-Seco, Francisco, Sánchez, José Salvador, Sotoca, José Martinez, Mollineda, Ramón Alberto |
| Zdroj: |
Structural, Syntactic & Statistical Pattern Recognition; 2006, p747-754, 8p |
| Abstrakt: |
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. Keywords: Pattern recognition, classification, nearest neighbor, prototype selection, editing. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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