A comparison of two approaches to classify with guaranteed performance

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

Volumn 4702 LNAI, Issue , 2007, Pages 288-299

  Vanderlooy, Stijn ^a   Sprinkhuizen Kuyper, Ida G ^b  

^a MAASTRICHT UNIVERSITY   (Netherlands)

^b RADBOUD UNIVERSITY NIJMEGEN   (Netherlands)

Author keywords

[No Author keywords available]

Indexed keywords

DATA MINING; DATABASE SYSTEMS; LEARNING SYSTEMS; USER INTERFACES;

ROC ISOMETRICS; TRANSDUCTIVE CONFIDENCE MACHINE;

CLASSIFICATION (OF INFORMATION);

EID: 38049160709     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-74976-9_28     Document Type: Conference Paper

References (10)

1. Vovk, V., Gammerman, A., Shafer, G.: Algorithmic Learning in a Random World. Springer, New York (2005)
2. Vanderlooy, S., Sprinkhuizen-Kuyper, I., Smirnov, E.: An analysis of reliable classifiers through ROC isometrics. In: Lachiche, N., Ferri, C., Macskassy, S., ICML (eds.) 2006 Workshop on ROC Analysis (ROCML 2006), Pittsburgh, USA, pp. 55-62 (2006)
3. Gammerman, A., Vovk, V.: Prediction algorithms and confidence measures based on algorithmic randomness theory. Theoretical Computer Science 287, 209-217 (2002)
4. Vanderlooy, S., van der Maaten, L., Sprinkhuizen-Kuyper, I.: Off-line learning with transductive confidence machines: an empirical evaluation. Technical Report 07-03, Universiteit Maastricht, Maastricht, The Netherlands (2007)
5. Proedrou, K., Nouretdinov, I., Vovk, V., Gammerman, A.: Transductive confidence machines for pattern recognition. Technical Report 01-02, Royal Holloway University of London, London, UK (2001)
6. Lachiche, N., Flach, P.: Improving accuracy and cost of two-class and multi-class probabilistic classifiers using ROC curves. In: Fawcett, T., Mishra, N. (eds.) 20th International Conference on Machine Learning (ICML 2003), pp. 416-423. AAAI Press, Washington, DC, USA (2003)
7. Provost, F., Fawcett, T.: Robust classification for imprecise environments. Machine Learning 42, 203-231 (2001)
8. Flach, P.: The geometry of ROC space: Understanding machine learning metrics through ROC isometrics. In: Fawcett, T., Mishra, N. (eds.) 20th International Conference on Machine Learning (ICML 2003), pp. 194-201. AAAI Press, Washington, DC, USA (2003)
9. Newman, D., Hettich, S., Blake, C., Merz, C.: UCI repository of machine learning databases (1998)
10. Guyon, I.: Data representation discovery workshop of the 20th international joint conference on neural networks (IJCNN 2007) (2007)