Error-Correcting Output Codes Library

In this paper, we present an open source Error-Correcting Output Codes (ECOC) library. The ECOC framework is a powerful tool to deal with multi-class categorization problems. This library contains both state-of-the-art coding (one-versus-one, one-versus-all, dense random, sparse random, DECOC, forest-ECOC, and ECOC-ONE) and decoding designs (hamming, euclidean, inverse hamming, laplacian, β-density, attenuated, loss-based, probabilistic kernel-based, and loss-weighted) with the parameters defined by the authors, as well as the option to include your own coding, decoding, and base classifier. [abs] [ pdf ][ bib ] [ code ] &copy JMLR 2010. ( edit, beta )

Authors

• Sergio Escalera CVC, UB, Spain
• Oriol Pujol
• Petia Radeva

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