A unified model for multilabel classification and ranking

Frontiers in Artificial Intelligence and Applications

Volumn 141, Issue , 2006, Pages 489-493

  Brinker, Klaus ^a   Fürnkranz, Johannes ^b   Hüllermeier, Eyke ^a  

^a OTTO VON GUERICKE UNIVERSITY   (Germany)

^b DARMSTADT UNIVERSITY OF TECHNOLOGY   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

LEARNING SYSTEMS; MACHINE LEARNING;

EXPRESSIVE POWER; LABEL RANKINGS; MULTI-LABEL CLASSIFICATIONS; MULTI-LABEL RANKINGS; MULTI-LABELS; NOVEL TECHNIQUES; PAIR-WISE COMPARISON; PREDEFINED SETS; UNIFIED MODELING; ZERO-POINT;

TEXT PROCESSING;

EID: 79951755700     PISSN: 09226389     EISSN: 18798314     Source Type: Book Series    
DOI: None     Document Type: Article

References (13)

1. Klaus Brinker and Eyke Hüllermeier, 'Calibrated Label-Ranking', Proceedings of the NIPS-2005 Workshop on Learning to Rank, S. Agarwal and C. Cortes and R. Herbrich (eds.), pp. 1-6, Whistler, BC, Canada, (2005).
2. Koby Crammer and Yoram Singer, 'A family of additive online algorithms for category ranking', Journal of Machine Learning Research, 3, 1025-1058, (2003).
3. Ofer Dekel, Christopher Manning, and Yoram Singer, 'Loglinear models for label ranking', in Advances in Neural Information Processing Systems 16, eds., Sebastian Thrun, Lawrence Saul, and Bernhard Schölkopf, MIT Press, Cambridge, MA, (2004).
4. André Elisseeff and Jason Weston, 'A kernel method for multilabelled classification', in Advances in Neural Information Processing Systems 14, eds., T. G. Dietterich, S. Becker, and Z. Ghahramani, pp. 681-687, Cambridge, MA, (2002). MIT Press.
5. Johannes Fürnkranz, 'Round robin classification', Journal of Machine Learning Research, 2, 721-747, (2002).
6. Johannes Fürnkranz and Eyke Hüllermeier, 'Pairwise preference learning and ranking', in Proceedings of the 14th European Conference on Machine Learning (ECML 2003), pp. 145-156, Cavtat, Croatia, (2003). Springer-Verlag.
7. Johannes Fürnkranz and Eyke Hüllermeier, 'Preference learning', Künstliche Intelligenz, 19(1), 60-61, (2005).
8. Sariel Har-Peled, Dan Roth, and Dav Zimak, 'Constraint classification: A new approach to multiclass classification and ranking', in Advances in Neural Information Processing Systems 15 (NIPS 2002), (2002).
9. Thorsten Joachims, 'Text categorization with support vector machines: Learning with many relevant features', in Proceedings of the European Conference on Machine Learning (ECML 1998), eds., Claire Nédellec and Céline Rouveirol, pp. 137-142, Berlin, (1998). Springer.
10. David D. Lewis. Reuters-21578 text categorization test collection. README file (V 1.2), available from http://www.research.att.com/~lewis/reuters21578/ README.txt, September 1997.
11. Robert E. Schapire and Yoram Singer, 'Improved boosting using confidence-rated predictions', Machine Learning, 37(3), 297-336, (1999).
12. Robert E. Schapire and Yoram Singer, 'Boos Texter: A boosting-based system for text categorization', Machine Learning, 39(2/3), 135-168, (2000).
13. Bernhard Schölkopf and Alexander J. Smola, Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond, MIT Press, Cambridge, MA, 2002.