Magical thinking in data mining: Lessons from CoIL challenge 2000

Proceedings of the Seventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

Volumn , Issue , 2001, Pages 426-431

  Elkan, Charles ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BACKPROPAGATION; LEARNING ALGORITHMS; NEURAL NETWORKS; STATISTICAL METHODS;

PREDICTIVE ACCURACY;

DATA MINING;

EID: 0035789256     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (11)

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3. C. Elkan. Boosting and naive Bayesian learning. Technical Report CS97-557, Department of Computer Science and Engineering, University of California, San Diego, 1997.
4. F. Farnstrom, J. Lewis, and C. Elkan. Scalability for clustering algorithms revisited. ACM SIGKDD Explorations, 2(1):51-57, 2000.
5. G. Gigerenzer. Adaptive Thinking: Rationality in the Real World. Oxford University Press, 2000.
6. T. S. Kuhn. The Structure of Scientific Revolutions. University of Chicago Press, 1962.
7. S. D. Silvey. Statistical Inference. John Wiley & Sons, Inc., 1975. Reprinted with corrections.
8. CoIL challenge 2000: The insurance company case. Technical Report 2000-09, Leiden Institute of Advanced Computer Science, Netherlands, 2000. Available at www.wi.leidenuniv.nl/̃putten/library/cc2000/report.html.
9. R. Wirth and J. Hipp. CRISP-DM: Towards a standard process model for data mining. In Proceedings of the Fourth International Conference on the Practical Application of Knowledge Discovery and Data Mining (PADD '00), pages 29-39, 2000.
10. B. Zadrozny and C. Elkan. Learning and making decisions when costs and probabilities are both unknown. In Proceedings of the Seventh International Conference on Knowledge Discovery and Data Mining. AAAI Press (distributed by MIT Press), Aug. 2001.
11. B. Zadrozny and C. Elkan. Obtaining calibrated probability estimates from decision trees and naive Bayesian classifiers. In Proceedings of the Eighteenth International Conference on Machine Learning, June 2001.