Heterogeneous Uncertainty Sampling for Supervised Learning

Proceedings of the 11th International Conference on Machine Learning, ICML 1994

Volumn , Issue , 1994, Pages 148-156

  Lewis, David D ^a   Catlett, Jason ^a  

^a LUCENT TECHNOLOGIES   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

MACHINE LEARNING; SOFTWARE TESTING;

CLASS LABELS; ERROR RATE; INDUCTION PROGRAMS; PROBABILISTICS; RANDOM SAMPLE; RULE INDUCTION; SAMPLING METHOD; UNCERTAINTY; UNCERTAINTY SAMPLINGS;

ITERATIVE METHODS;

EID: 85124125604     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1016/B978-1-55860-335-6.50026-X     Document Type: Conference Paper

References (36)

1. [ 1 ] Dana Angluin. Queries and concept learning. Machine Learning, 2:319-342,1988.
2. I. Bratko, I. Mozetic, and N. Lavrac. KARDIO: a study in deep and qualitative knowledge for expert systems. MIT Press, Cambridge, Massachusetts, 1989.
3. Leo Breiman, Jerome H. Friedman, Richard A. Olshen, and Charles J. Stone. Classification and Regression Trees. Wadsworth, Belmont, CA, 1984.
4. J. Catlett. Megainduction: a test flight. In Machine Learning: Proceedings of the Eigth International Workshop, pages 596-599, San Mateo, CA, 1991. Morgan Kaufmann.
5. William G. Cochran. Sampling Techniques. John Wiley & Sons, New York, 3rd edition, 1977.
6. David Cohn, Les Atlas, and Richard Ladner. Improving generalization with self-directed learning, 1992. To appear in Machine Learning.
7. Stuart L. Crawford, Robert M. Fung, Lee A. Appelbaum, and Richard M. Tong. Classification trees for information retrieval. In Eighth International Workshop on Machine Learning, pages 245-249,1991.
8. Daniel T. Davis and Jenq-Neng Hwang. Attentional focus training by boundary region data selection. In International Joint Conference on Neural Networks, pages 1-676 to 1-681, Baltimore, MD, June 7-11 1992.
9. James P. Egan. Signal Detection Theory and ROC Analysis. Academic Press, New York, 1975.
10. Y. Freund, H. S. Seung, E. Shamir, and N. Tishby. Information, prediction, and query by committee. In Advances in Neural Information Processing Systems 5, San Mateo, CA, 1992. Morgan Kaufmann.
11. William A. Gale, Kenneth W. Church, and David Yarowsky. A method for disambiguating word senses in a large corpus. Computers and the Humanities, 26:415^139,1993.
12. B. K. Ghosh. A brief history of sequential analysis. In B. K. Ghosh and P. K. Sen, editors, Handbook of Sequential Analysis, chapter 1, pages 1-19. Marcel Dekker, New York, 1991.
13. Norm Goldstein, editor. The Associated Press Style-book and Libel Manual. Addison-Wesley, Reading, MA, 1992.
14. Donna Harman. Ranking algorithms. In William B. Frakes and Ricardo Baeza-Yates, editors, Information Retrieval: Data Structures and Algorithms, pages 363-392. Prentice Hall, Englewood Cliffs, NJ, 1992.
15. Peter E. Hart. The condensed nearest neighbor rule. IEEE Transactions on Information Theory, IT-14:515-516, May 1968. Reprinted in Agrawala, Machine Recognition of Patterns, IEEE Press, New York, 1977.
16. [ 16] Jenq-Neng Hwang, Jai J. Choi, Seho Oh, and Robert J. Marks II. Query-based learning applied to partially trained multilayer perceptrons. IEEE Transactions on Neural Networks, 2(1): 131-136, January 1991.
17. Igor Kononerko, Ivan Bratko, and Esidija Roskar. Experiments in automatic learning of medical diagnostic rules. Technical report, Jozef Stefan Institute, Ljubljana, Slovenia, 1984.
18. David D. Lewis and William A. Gale. Training text classifiers by uncertainty sampling. In Seventeenth Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 1994. To appear.
19. David D. Lewis and Philip J. Hayes. Editorial. ACM Transactions on Information Systems. Special Issue on Text Categorization, 1994. To appear.
20. David J. C. MacKay. The evidence framework applied to classification networks. Neural Computation, 4:720-736,1992.
21. David J. C. MacKay. Information-based objective functions for active data selection. Neural Computation, 4(4):589-603,1992.
22. Michel Manage Knowledge intensive induction. In Machine Learning: Proceedings of the Sixth International Workshop, pages 151-155,1989.
23. P. McCullagh and J. A. Nelder. Generalized Linear Models. Chapman & Hall, London, 2nd edition, 1989.
24. Tom M. Mitchell. Generalization as search. Artificial Intelligence, 18:203-226,1982.
25. Mark Plutowski and Halbert White. Selecting concise training sets from clean data. IEEE Transactions on Neural Networks, 4(2):305-318, March 1993.
26. J. R. Quinlan. Discovering rules by induction from large collections of examples. In Expert systems in the micro-electronic age, Edinburgh, UK, 1979. Edinburgh University Press.
27. J. Ross Quinlan. C4.5: Programs for Machine Learning. Morgan Kaufmann, San Mateo, CA, 1993.
28. J.R. Quinlan. Decision trees as probabilistic classifiers. In Proceedings of the Fourth International Workshop on Machine Learning, pages 31-37, Irvine, California, 1987.
29. Gerard Salton. Automatic Text Processing: The Transformation, Analysis, and Retrieval of Information by Computer. Addison-Wesley, Reading, MA, 1989.
30. Claude Sammut, Scott Hurst, Dana Kedzier, and Donald Michie. Learning to fly. In Ninth International Workshop on Machine Learning, pages 385-393,1992.
31. H. S. Seung, M. Opper, and H. Sompolinsky. Query by committee. In Proceedings of the Fifth Annual ACM Workshop on Computational Learning Theory, pages 287-294,1992.
32. Bikas Kumar Sinha. Sequential methods for finite populations. In B. K. Ghosh and P. K. Sen, editors, Handbook of Sequential Analysis, chapter 1, pages 1-19. Marcel Dekker, New York, 1991.
33. Paul E. Utgoff. Improved training via incremental learning. In Sixth International Workshop on Machine Learning, pages 362-365,1989.
34. Sholom M. Weiss, Robert S. Galen, and Prasad V. Tadepalli. Maximizing the predictive value of production rules. Artificial Intelligence, 45(l-2):47-71, September 1990.
35. P. H. Winston. Learning structural descriptions from examples. In P. H. Winston, editor, The Psychology of Computer Vision, pages 157-209. McGraw-Hill, New York, 1975.
36. J. Wirth and J. Catlett. Costs and benefits of windowing in ID3. In Proceedings of the Fifth International Conference on Machine Learning, Ann Arbor, Michigan, 1988. Morgan Kaufmann.