Introducing the separability matrix for error correcting output codes coding

Authors:
Miguel Ángel Bautista;Oriol Pujol;Xavier Baró;Sergio Escalera
Affiliations:
Applied Math and Analisis Dept., University of Barcelona, Barcelona, Spain and Computer Vision Center, Bellaterra, Spain;Applied Math and Analisis Dept., University of Barcelona, Barcelona, Spain and Computer Vision Center, Bellaterra, Spain;Applied Math and Analisis Dept., University of Barcelona, Barcelona, Spain and Computer Vision Center, Bellaterra, Spain and Computer Science, Multimedia and Telecommunications Dept., Universitat ...;Applied Math and Analisis Dept., University of Barcelona, Barcelona, Spain and Computer Vision Center, Bellaterra, Spain
Venue:
MCS'11 Proceedings of the 10th international conference on Multiple classifier systems
Year:
2011

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Abstract

Error Correcting Output Codes (ECOC) have demonstrate to be a powerful tool for treating multi-class problems. Nevertheless, predefined ECOC designs may not benefit from Error-correcting principles for particular multi-class data. In this paper, we introduce the Separability matrix as a tool to study and enhance designs for ECOC coding. In addition, a novel problem-dependent coding design based on the Separability matrix is tested over a wide set of challenging multi-class problems, obtaining very satisfactory results.