In this work a novel editing technique is proposed. The basic idea of the algorithm is to reward patterns that contribute to a correct classification and to punish those that provide a wrong one. Reward-punishment is performed according to two criteria: the former operates at very local level while the latter analyses the training set at coarser scales in a multi-resolution fashion. A score is calculated for each pattern according to the two criteria and patterns whose score is lower than a predefined threshold are edited out. Experiments carried out on two difficult classification problems show the superiority of this method with respect to other well known approaches.

Reward-Punishment Editing

FRANCO, ANNALISA;MALTONI, DAVIDE;NANNI, LORIS
2004

Abstract

In this work a novel editing technique is proposed. The basic idea of the algorithm is to reward patterns that contribute to a correct classification and to punish those that provide a wrong one. Reward-punishment is performed according to two criteria: the former operates at very local level while the latter analyses the training set at coarser scales in a multi-resolution fashion. A score is calculated for each pattern according to the two criteria and patterns whose score is lower than a predefined threshold are edited out. Experiments carried out on two difficult classification problems show the superiority of this method with respect to other well known approaches.
Proceedings of the 17th International Conference on Pattern Recognition (ICPR 2004)
424
427
A. Franco; D. Maltoni; L. Nanni
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/6560
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