Single-stacking conformity approach to reliable classification

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

Volumn 6304 LNAI, Issue , 2010, Pages 161-170

  Smirnov, Evgueni ^a   Nikolaev, Nikolay ^b   Nalbantov, Georgi ^a  

^a MAASTRICHT UNIVERSITY   (Netherlands)

^b UNIVERSITY OF LONDON   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFIERS; ROADS AND STREETS;

ARTIFICIAL INTELLIGENCE;

EID: 78149259862     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-15431-7_17     Document Type: Conference Paper

References (28)

1. Baskiotis, N., Sebag, M.: C4.5 competence map: a phase transition-inspired approach. In: Proceedings of the 21th International Conference on Machine Learning (ICML 2004), pp. 73-80 (2004)
2. Bay, S., Pazzani, M.: Characterizing model errors and differences. In: Proceedings of the 17th International Conference on Machine Learning (ICML 2000), pp. 196-201 (2000)
3. Bosnic, Z., Kononenko, I.: An overview of advances in reliability estimation of individual predictions in machine learning. Intell. Data Anal. 13(2), 385-401 (2009)
4. Domingos, P., Pazzani, M.: Beyond independence: conditions for the optimality of the simple bayesian classifier. In: Proceedings of the Thirteenth International Conference on Machine Learning (ICML 1996), pp. 105-112. Morgan Kaufmann, San Francisco (1996)
5. Duda, R., Hart, P., Stork, D.: Pattern Classification, 2nd edn. Wiley, Chichester (2000)
6. Fawcett, T.: Roc graphs: Notes and practical considerations for researchers. Tech. Rep. HPL-2003-4, HP Laboratories (2003), http://citeseer.ist. psu.edu/fawcett04roc.html
7. Ferri, C., Hernndez-Orallo, J.: Cautious classifiers. In: Proceedings of the 1st International Workshop on ROC Analysis in Artificial Intelligence (ROCAI 2004), pp. 27-36 (2004)
8. Friedel, C., Ruckert, U., Kramer, S.: Cost curves for abstaining classifiers. In: Lachiche, N., Ferri, C., Macskassy, S. (eds.) Proceedings of the ICML 2006 Workshop on ROC Analysis (ROCML 2006), Pittsburgh, USA (June 29, 2006)
9. Hullermeier, E.: Instance-based prediction with guaranteed confidence. In: Proceedings of the 16th European Conference on Artificial Intelligence (ECAI 2004), pp. 97-101 (2004)
10. Kaptein, A.: Meta-Classifier Approach to Reliable Text Classification. Master's thesis, Maastricht University, The Netherlands (2005)
11. Kukar, M.: Quality assessment of individual classifications in machine learning and data mining. Knowl. Inf. Syst. 9(3), 364-384 (2006)
12. Perner, P.: Proceedings of 10th Industrial Conference on Data Mining (ICDM 2010), Berlin, Germany. July 12-14, IBaI Report (2010)
13. Proedru, K., Nouretdinov, I., Vovk, V., Gammerman, A.: Transductive confidence machines for pattern recognition. In: Elomaa, T., Mannila, H., Toivonen, H. (eds.) ECML 2002. LNCS (LNAI), vol. 2430, pp. 381-390. Springer, Heidelberg (2002)
14. Quinlan, J.R.: C4.5: programs for machine learning. Morgan Kaufmann, San Mateo (1993)
15. Saunders, C., Gammerman, A., Vovk, V.: Transduction with confidence and credibility. In: Proceedings of the 16th International Joint Conference on Artificial Intelligence (IJCAI 1999), pp. 722-726 (1999)
16. Shafer, G., Vovk, V.: A tutorial on conformal prediction. Journal of Machine Learning Research 9, 371-421 (2008)
17. Smirnov, E., Nalbantov, G., Nikolaev, N.: k-Version-space multi-class classification based on k-consistency tests. In: Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2010 (2010) (accepted)
18. Smirnov, E., Kaptein, A.: Theoretical and experimental study of a meta-typicalness approach for reliable classification. In: Proceedings of the IEEE International Workshop on Reliability Issues in Knowledge Discovery (RIKD 2006), pp. 739-743. IEEE Computer Society, Los Alamitos (2006)
19. Smirnov, E., Nalbantov, G., Kaptein, A.: Meta-conformity approach to reliable classification. Intell. Data Anal. 13(6), 901-915 (2009)
20. Smirnov, E., Sprinkhuizen-Kuyper, I., Nalbantov, G., Vanderlooy, S.: Version space support vector machines. In: Proceedings of the 17th European Conference on Artificial Intelligence (ECAI 2006), pp. 809-810 (2006)
21. Smirnov, E., Sprinkhuizen-Kuyper, I., Nikolaev, N.: Generalizing version space support vector machines for non-separable data. In: Proceedings of the IEEE International Workshop on Reliability Issues in Knowledge Discovery (RIKD 2006), pp. 744-748. IEEE Computer Society, Los Alamitos (2006)
22. Smirnov, E., Vanderlooy, S., Sprinkhuizen-Kuyper, I.: Meta-typicalness approach to reliable classification. In: Proceedings of the 17th European Conference on Artificial Intelligence (ECAI 2006), pp. 811-812 (2006)
23. Tzikas, D., Kukar, M., Likas, A.: Transductive reliability estimation for kernel based classifiers. In: R. Berthold, M., Shawe-Taylor, J., Lavrač, N. (eds.) IDA 2007. LNCS, vol. 4723, pp. 37-47. Springer, Heidelberg (2007)
24. Vanderlooy, S., Sprinkhuizen-Kuyper, I., Smirnov, E.: An analysis of reliable classifiers through ROC isometrics. In: Lachiche, N., Ferri, C., Macskassy, S. (eds.) Proceedings of the ICML 2006 Workshop on ROC Analysis (ROCML 2006), Pittsburgh, USA, June 29, pp. 55-62 (2006)
25. Vanderlooy, S., Sprinkhuizen-Kuyper, I., Smirnov, E.: Reliable classifiers in ROC space. In: Saeys, Y., Tsiporkova, E., Baets, B.D., de Peer, Y.V. (eds.) Proceedings of the 15th Annual Machine Learning Conference of Belgium and the Netherlands (BENELEARN 2006), Ghent, Belgium, May 11-22, pp. 113-120 (2006)
26. Vapnik, V.: Statistical Learning Theory. John Wiley, NY (1998)
27. Vovk, V., Gammerman, A., Shafer, G.: Algorithmic Learning in a Random World. Springer, Heidelberg (2005)
28. Wolpert, D.: Stacked generalization. Neural Networks 5, 241-260 (1992)