Multilayer perceptron for label ranking

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

Volumn 7553 LNCS, Issue PART 2, 2012, Pages 25-32

  Ribeiro, Geraldina ^a   Duivesteijn, Wouter ^b   Soares, Carlos ^c   Knobbe, Arno ^b  

^a UNIVERSITY OF PORTO   (Portugal)

^b LEIDEN UNIVERSITY   (Netherlands)

^c UNIVERSITY OF PORTO   (Portugal)

Author keywords

back propagation; Label ranking; multilayer perceptron

Indexed keywords

BENCH-MARK PROBLEMS; ERROR SIGNAL; FINANCIAL ANALYSTS; FINITE SET; MULTI LAYER PERCEPTRON; RANKING PROBLEMS; SINGLE-VALUE;

BACKPROPAGATION; LEARNING SYSTEMS;

NEURAL NETWORKS;

EID: 84867689257     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-33266-1_4     Document Type: Conference Paper

References (15)

1. Aiguzhinov, A., Soares, C., Serra, A.P.: A Similarity-Based Adaptation of Naive Bayes for Label Ranking: Application to the Metalearning Problem of Algorithm Recommendation. In: Discovery Science (2010)
2. Vembu, S., Gärtner, T.: Label Ranking Algorithms: A Survey. In: Fürnkranz, J., Hüllermeier, E. (eds.) Preference Learning. Springer (2010)
3. Hüllermeier, E., Fürnkranz, J.: On loss functions in label ranking and risk minimization by pairwise learning. JCSS 76(1), 49-62 (2010)
4. Kanda, J., Carvalho, A.C.P.L.F., Hruschka, E.R., Soares, C.: Using Meta-learning to Classify Traveling Salesman Problems. In: SBRN (2010)
5. Brinker, K., Hüllermeier, E.: Label Ranking in Case-Based Reasoning. In: Weber, R.O., Richter, M.M. (eds.) ICCBR 2007. LNCS (LNAI), vol. 4626, pp. 77-91. Springer, Heidelberg (2007)
6. Dekel, O., Manning, C.D., Singer, Y.: Log-linear models for label ranking. In: Advances in Neural Information Processing Systems (2003)
7. Hülermeier, E., Fürnkranz, J., Cheng, W., Brinker, K.: Label ranking by learning pairwise preferences. Artif. Intell., 1897-1916 (2008)
8. Cheng, W., Dembczynski, K., Hüllermeier, E.: Label Ranking Methods based on the Plackett-Luce Model. In: ICML (2010)
9. Cheng, W., Huhn, J.C., Hüllermeier, E.: Decision tree and instance-based learning for label ranking. In: ICML (2009)
10. de Sá, C.R., Soares, C., Jorge, A.M., Azevedo, P., Costa, J.: Mining Association Rules for Label Ranking. In: Huang, J.Z., Cao, L., Srivastava, J. (eds.) PAKDD 2011, Part II. LNCS, vol. 6635, pp. 432-443. Springer, Heidelberg (2011)
11. Haykin, S.: Neural Networks: a comprehensive foundation, 2nd edn (1998)
12. KEBI Data Repository, http://www.uni-marburg.de/fb12/kebi/research/ repository
13. Demǎr, J.: Statistical comparisons of classifiers over multiple data sets. Journal of Machine Learning Research 7, 1-30 (2006)
14. Klösgen, W.: Subgroup Discovery. In: Handbook of Data Mining and Knowledge Discovery, ch. 16.3. Oxford University Press, New York (2002)
15. Pieters, B.F.I., Knobbe, A., Džeroski, S.: Subgroup Discovery in Ranked Data, with an Application to Gene Set Enrichment. In: Proc. Preference Learning Workshop (PL 2010) at ECML PKDD (2010)