On minimizing the position error in label ranking

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

Volumn 4701 LNAI, Issue , 2007, Pages 583-590

  Hüllermeier, Eyke ^a   Fürnkranz, Johannes ^b  

^a PHILIPPS UNIVERSITY MARBURG   (Germany)

^b DARMSTADT UNIVERSITY OF TECHNOLOGY   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; CLASSIFICATION (OF INFORMATION); LEARNING SYSTEMS; PROBLEM SOLVING;

CLASSIFICATION LEARNING; LABEL RANKING;

ERROR CORRECTION;

EID: 38049181290     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-74958-5_56     Document Type: Conference Paper

References (7)

1. Alonso, C., Rodríguez, J.J., Pulido, B.: Enhancing consistency based diagnosis with machine learning techniques. In: Conejo, R., Urretavizcaya, M., Pérez-de-la-Cruz, J.-L. (eds.) Current Topics in Artificial Intelligence. LNCS (LNAI), vol. 3040, pp. 312-321. Springer, Heidelberg (2004)
2. Fürnkranz, J.: Round robin classification. J. of Mach. Learn. Res. 2, 721-747 (2002)
3. Fürnkranz, J., Hüllermeier, E.: Pairwise preference learning and ranking. In: Lavrač, N., Gamberger, D., Todorovski, L., Blockeel, H. (eds.) ECML 2003. LNCS (LNAI), vol. 2837, Springer, Heidelberg (2003)
4. Har-Peled, S., Roth, D., Zimak, D.: Constraint classification: a new approach to multiclass classification. In: Cesa-Bianchi, N., Numao, M., Reischuk, R. (eds.) ALT 2002. LNCS (LNAI), vol. 2533, pp. 365-379. Springer, Heidelberg (2002)
5. Hüllermeier, E., Fürnkranz, J.: Learning label preferences: Ranking error versus position error. In: Famili, A.F., Kok, J.N., Peña, J.M., Siebes, A., Feelders, A. (eds.) IDA 2005. LNCS, vol. 3646, Springer, Heidelberg (2005)
6. Hüllermeier, E., Fürnkranz, J.: On minimizing the position error in label ranking. Technical Report TUD-KE-2007-04, TU Darmstadt (2007)
7. Wu, T.F., Lin, C.J., Weng, R.C.: Probability estimates for multi-class classification by pairwise coupling. J. Machine Learning Res. 5, 975-1005 (2004)