Polychotomous classification with pairwise classifiers: A new voting principle

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 2709, Issue , 2003, Pages 115-124

  Cutzu, Florin ^a  

^a INDIANA UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTERS;

CLASS J; CLASSIFICATION MODELS; PAIRWISE CLASSIFIERS; UNKNOWN CLASS;

ARTIFICIAL INTELLIGENCE;

EID: 35248857943     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-44938-8_12     Document Type: Article

References (7)

1. Erin L. Allwein, Robert E. Schapire, and Yoram Singer. Reducing multiclass to binary: A unifying approach for margin classifiers. In Proc. 17th International Conf. on Machine Learning, pages 9-16. Morgan Kaufmann, San Francisco, CA, 2000.
2. Jerome H. Friedman. Another approach to polychotomous classification. Technical report, Stanford University, 1996.
3. Trevor Hastie and Robert Tibshirani. Classification by pairwise coupling. In Michael I. Jordan, Michael J. Kearns, and Sara A. Solla, editors, Advances in Neural Information Processing Systems, volume 10. The MIT Press, 1998.
4. Eddy Mayoraz and Ethem Alpaydin. Support vector machines for multi-class classification. In IWANN (2), pages 833-842, 1999.
5. Volker Roth. Probabilistic discriminative kernel classifiers for multi-class problems. Lecture Notes in Computer Science, 2191:246-266, 2001.
6. Jürgen Schürmann. Patern Classification. A Unified View of Statistical and Neural Principles. John Wiley & Sons, Inc, New York, NA, 1996.
7. B. Zadrozny. Reducing multiclass to binary by coupling probability estimates, 2001.