Error Correcting Output Coding is a well established technique to decompose a multi-class classification problem into a set of two-class problems. However, a point not yet considered in the research is how to apply this method to a cost- sensitive classification that represents a significant aspect in many real problems. In this paper we propose a novel method for building cost-sensitive ECOC multi-class classifiers. Starting from the cost matrix for the multi-class problem and from the code matrix employed, a cost matrix is extracted for each of the binary subproblems induced by the coding matrix. As a consequence, it is possible to tune the single two-class classifier according to the cost matrix obtained and achieve an output from all the dichotomizers which takes into account the requirements of the original multi-class cost matrix. To evaluate the effectiveness of the method, a large number of tests has been performed on real data sets. The first experimental results show that the proposed approach is suitable for future developments in cost-sensitive application.

A Method for Designing Cost sensitive ECOC

F. TORTORELLA
Methodology
2004-01-01

Abstract

Error Correcting Output Coding is a well established technique to decompose a multi-class classification problem into a set of two-class problems. However, a point not yet considered in the research is how to apply this method to a cost- sensitive classification that represents a significant aspect in many real problems. In this paper we propose a novel method for building cost-sensitive ECOC multi-class classifiers. Starting from the cost matrix for the multi-class problem and from the code matrix employed, a cost matrix is extracted for each of the binary subproblems induced by the coding matrix. As a consequence, it is possible to tune the single two-class classifier according to the cost matrix obtained and achieve an output from all the dichotomizers which takes into account the requirements of the original multi-class cost matrix. To evaluate the effectiveness of the method, a large number of tests has been performed on real data sets. The first experimental results show that the proposed approach is suitable for future developments in cost-sensitive application.
2004
9783540221449
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11386/4721719
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 0
  • ???jsp.display-item.citation.isi??? 0
social impact