In this work 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, Beta-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.
- Changes to previous version:
Initial Announcement on mloss.org.
- BibTeX Entry: Download
- Corresponding Paper BibTeX Entry: Download
- URL: Project Homepage
- JMLR MLOSS PaperURL: JMLR-MLOSS Paper Homepage
- Supported Operating Systems: Platform Independent
- Data Formats: Matlab, Octave
- Tags: Ensemble Of Classifiers, Error Correcting Output Codes, Multiclass Classification
- Archive: download here
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