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.
Titolo: | Reward-Punishment Editing |
Autore/i: | FRANCO, ANNALISA; MALTONI, DAVIDE; NANNI, LORIS |
Autore/i Unibo: | |
Anno: | 2004 |
Titolo del libro: | Proceedings of the 17th International Conference on Pattern Recognition (ICPR 2004) |
Pagina iniziale: | 424 |
Pagina finale: | 427 |
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. |
Data prodotto definitivo in UGOV: | 28-set-2005 |
Appare nelle tipologie: | 4.01 Contributo in Atti di convegno |