Pairwise learning of multilabel classifications with perceptrons

Proceedings of the International Joint Conference on Neural Networks

Volumn , Issue , 2008, Pages 2899-2906

  Mencía, Eneldo Loza ^a   Fürnkranz, Johannes ^a  

^a DARMSTADT UNIVERSITY OF TECHNOLOGY   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL COMPLEXITY; CYBERNETICS; LOCOMOTIVES; PATTERN RECOGNITION SYSTEMS; RAILROAD CARS; ULSI CIRCUITS;

AVERAGE NUMBERS; BINARY CLASSIFIERS; DATA SETS; INCREMENTAL TRAINING ALGORITHMS; MULTI CLASSES; MULTILABEL; PERCEPTRON; PREDICTION TASKS; SUBSTANTIAL IMPROVEMENTS; TRAINING EXAMPLES; TRAINING SIGNALS;

NEURAL NETWORKS;

EID: 56349095271     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IJCNN.2008.4634206     Document Type: Conference Paper

References (26)

1. Erin L. Allwein, Robert E. Schapire, and Yoram Singer. Reducing multiclass to binary: A unifying approach, for margin classifiers. In Proceedings of the. 17th International Conference on Machine Learning (ICML 2000), pages 9-16, 2000.
2. Christopher M. Bishop. Neural Networks for Pattern. Recognition. Oxford University Press, 1995.
3. Klaus Brinker, Johannes Fürnkranz, and Eyke Hüllermeier. A Unified Model for Multilabel Classification and Ranking. In Proceedings of the 17th European Conference on Artificial Intelligence (ECAI-06), 2006.
4. Koby Crammer and Yoram Singer. A Family of Additive Online Algorithms for Category Ranking. Journal of Machine Learning Research, 3(6):1025-1058, 2003.
5. Koby Crammer, Ofer Dekel, Joseph Keshet, Shai Shalev-Shwartz, and Yoram Singer. Online passive-aggressive algorithms. Journal of Machine Learning Research, 7:551-585, 2006.
6. Janez Demšar. Statistical comparisons of classifiers over multiple data sets. Journal of Machine Learning Research, 7:1-30, 2006.
7. Andre Elisseeff and Jason Weston. A kernel method for multilabelled classification. In Advances in Neural Information Processing Systems, volume 14, pages 681-687, 2001.
8. Yoav Freund and Robert E. Schapire. Large Margin Classification using the Perceptron Algorithm. Machine Learning, 37(3):277-296, 1999.
9. Johannes Fürnkranz. Round Robin Classification. Journal of Machine Learning Research, 2:721-747, 2002.
10. Johannes Fürnkranz and Eyke Hüllermeier. Pairwise Preference Learning and Ranking. In Proceedings of the 14th European Conference on Machine Learning (ECML-03), pages 145-156, 2003.
11. Chih-Wei Hsu and Chin-Jen Lin. A Comparison of Methods for Multi-class Support. Vector Machines. IEEE Transactions on Neural Networks, 13(2):415-425, 2002.
12. Thorsten Joachims. Training Linear SVMs in Linear Time. In Proceedings of the Twelfth. ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 217-226, 2006.
13. Roni Khardon and Gabriel Wachman. Noise tolerant variants of the perceptron algorithm. Journal of Machine Learning Research, 8: 227-248, 2007.
14. Stefan Knerr, Léon Personnaz, and Gérard Dreyfus. Handwritten Digit Recognition by Neural Networks with Single-Layer Training. IEEE Transactions on Neural Networks, 3(6):962-968, 1992.
15. David D. Lewis, Yiming Yang, Tony G. Rose, and Fan Li. RCV1: A New Benchmark Collection for Text Categorization Research. Journal of Machine Learning Research, 5:361-397, 2004.
16. Yaoyong Li, Hugo Zaragoza, Ralf Herbrich, John Shawe-Taylor, and Jaz S. Kandola. The Perceptron Algorithm with Uneven Margins. In Machine Learning, Proceedings of the Nineteenth International Conference (ICML 2002), pages 379-386, 2002.
17. Eneldo Loza Mencía and Johannes Fürnkranz. Pairwise learning of multilabel classifications with perceptrons. Technical Report TUD-KE-2007-05, Knowledge Engineering Group, TU Darmstadt, 2007.
18. Sang-Hyeun Park and Johannes Fürnkranz. Efficient pairwise classifciation. In Proceedings of 18th European Conference on Machine Learning (ECML-07), pages 658-665, Warsaw, Poland, 2007.
19. David Price, Stefan Knerr, Leon Personnaz, and Gerard Dreyfus. Pairwise Neural Network Classifiers with Probabilistic Outputs. In Advances in Neural Information. Processing Systems, volume 7, pages 1109-1116. The MIT Press, 1995.
20. Frank Rosenblatt. The perceptron: a probabilistic model for information storage and organization in the brain. Psychological Review, 65(6):386-408, 1958.
21. Fabrizio Sebastiani. Machine learning in automated text categorization. ACM Computing Surveys, 34(1):1-47, 2002.
22. Shai. Shalev-Shwartz and Yoram Singer. A New Perspective on an Old Perceptron Algorithm. In Learning Theory, 18th Annual Conference on Learning Theory (COLT 2005), pages 264-278. Springer, 2005.
23. Jan-Nikolas Sulzmann, Johannes Fürnkranz, and Eyke Hüllermeier. On pairwise naive bayes classifiers. In Proceedings of the 18th European Conference on Machine Learning (ECML 2007), pages 371-381, Warsaw, Poland, 2007.
24. Petroula Tsampouka and John Shawe-Taylor. Approximate maximum margin algorithms with rules controlled by the number of mistakes. In Machine Learning, Proceedings of the Twenty-Fourth International Conference on Machine Learning(ICML 2007), volume 227, pages 903-910, 2007.
25. Adriano Veloso, Wagner Meira Jr., Marcos André Gonçalves, and Mohammed Zaki. Multi-label lazy associative classification. In Knowledge Discovery in Databases: PKDD 2007, 11th European Conference on Principles and Practice of Knowledge Discovery in Databases, volume 4702, pages 605-612, 2007.
26. Min-Ling Zhang and Zhi-Hua Zhou. Multilabel neural networks with applications to functional genomics and text categorization. IEEE Transactions on Knowledge and Data Engineering, 18(10): 1338-1351, 2006.