Learning Rare Class Footprints: the REFLEX Algorithm
作者： Ray J. Hickey , N. Ireland
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摘要: An r-contour footprint is a set of individuals each whom has propensity at least r belonging to rare class. The properties footprints are summarized. algorithm, REFLEX, proposed for extracting from an induced decision tree. Results initial experiments comparing REFLEX mestimation Laplace smoothing show that both algorithms deliver broadly similar performance different contours. Unlike Laplace, does not require extensive tuning. When high class disjuncts exist (> 50%), perform better on pruned trees.
参考文章(11)
Robert C. Holte, Bruce W. Porter, Liane E. Acker, Concept learning and the problem of small disjuncts international joint conference on artificial intelligence. pp. 813- 818 ,(1989)
I Bratko, T. Niblett, Learning decision rules in noisy domains Proceedings of Expert Systems '86, The 6Th Annual Technical Conference on Research and development in expert systems III. pp. 25- 34 ,(1987)
Charles Elkan, The foundations of cost-sensitive learning international joint conference on artificial intelligence. pp. 973- 978 ,(2001)
David D. Jensen, Paul R. Cohen, Multiple Comparisons in Induction Algorithms Machine Learning. ,vol. 38, pp. 309- 338 ,(2000) , 10.1023/A:1007631014630
M. A. Bramer, R. W. Milne, Research and development in expert systems IX : proceedings of Expert Systems 92, the Twelfth Annual Technical Conference of the British Computer Society Specialist group on Expert Systems, London, December 1992 Cambridge University Press. ,(1993) , 10.1017/CBO9780511569944
Foster Provost, R Fawcett, T, Kohavi, The Case against Accuracy Estimation for Comparing Induction Algorithms international conference on machine learning. pp. 445- 453 ,(1998)
Bojan Cestnik, Ivan Bratko, On estimating probabilities in tree pruning Lecture Notes in Computer Science. pp. 138- 150 ,(1991) , 10.1007/BFB0017010
Nathalie Japkowicz, Shaju Stephen, The class imbalance problem: A systematic study intelligent data analysis. ,vol. 6, pp. 429- 449 ,(2002) , 10.3233/IDA-2002-6504
J.R. Quinlan, Induction of Decision Trees Machine Learning. ,vol. 1, pp. 81- 106 ,(1986) , 10.1023/A:1022643204877
Chris Drummond, Robert C. Holte, Explicitly representing expected cost: an alternative to ROC representation knowledge discovery and data mining. pp. 198- 207 ,(2000) , 10.1145/347090.347126