Incremental Feature Selection

Applied Intelligence

Volumn 9, Issue 3, 1998, Pages 217-230

  Liu, Huan ^a,b,c,d,e,f   Setiono, Rudy ^a,g,h  

^a NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

^b UNIVERSITY OF SOUTHERN CALIFORNIA   (United States)

^c SHANGHAI JIAO TONG UNIVERSITY   (China)

^d Telecom Australia Research Lab   (Australia)

^e IEEE   (Singapore)

^f ACM Society   (Singapore)

^g EASTERN MICHIGAN UNIVERSITY   (United States)

^h UNIVERSITY OF WISCONSIN MADISON   (United States)

Author keywords

Dimensionality reduction; Feature selection; Machine learning; Pattern recognition

Indexed keywords

LEARNING ALGORITHMS; LEARNING SYSTEMS; OPTIMIZATION; PROBABILISTIC LOGICS;

INCREMENTAL FEATURE SELECTION;

FEATURE EXTRACTION;

EID: 0032206482     PISSN: 0924669X     EISSN: None     Source Type: Journal    
DOI: 10.1023/A:1008363719778     Document Type: Article

References (30)

1. D. Koller and M. Sahami, "Toward optimal feature selection," in Machine Learning: Proceedings of the Thirteenth International Conference, edited by L. Saitta, Morgan Kaufmann Publishers, 1996. pp. 284-292.
2. D.W. Aha, "Tolerating noisy, irrelevant and novel attributes in instance-bassed learning algorithm," International Journal of Man-Machine Studies, vol. 36, no. 1, 1992.
3. P.M. Narendra and K. Fukunaga, "A branch and bound algorithm for feature subset selection," IEEE Trans, on Computer, vol. C-26, no. 9, pp. 917-922, September 1977.
4. W. Siedlecki and J. Sklansky, "On automatic feature selection," International Journal of Pattern Recognition and Artificial Intelligence, vol. 2, pp. 197-220, 1988.
5. M. Dash and H. Liu, "Feature selection methods for classifications," Intelligent Data Analysis: An International Journal, vol. 1, no. 3, 1997.
6. A. Jain and D. Zongker, "Feature selection: Evaluation, application, and small sample performance," IEEE Trans, on Pattern Analysis and Machine Intelligence, vol. 19, no. 2, pp. 153-158, 1997.
7. G.H. John, R. Kohavi, and K. Pfleger, "Irrelevant feature and the subset selection problem," in Machine Learning: Proceedings of the Eleventh International Conference, Morgan Kaufmann Publisher, 1994, pp. 121-129.
8. P. Langley, "Selection of relevant features in machine learning," in Proceedings of the AAAI Fall Symposium on Relevance, AAAI Press, 1994.
9. N. Wyse, R. Dubes, and A.K. Jain, "A critical evaluation of intrinsic dimensionality algorithms," in Pattern Recognition in Practice, edited by E.S. Gelsema and L.N. Kanal, Morgan Kaufmann Publishers, Inc., pp. 415-425, 1980.
10. P.A. Devijver and J. Kittler, Pattern Recognition: A Statistical Approach, Prentice Hall International, 1982.
11. K. Kira and L.A. Rendell, "The feature selection problem: Traditional methods and a new algorithm," in Proceedings of the Ninth National Conference on Artificial Intelligence, AAAI Press/The MIT Press, 1992, pp. 129-134.
12. H. Almuallim and T.G. Dietterich, "Learning Boolean concepts in the presence of many irrelevant features," Artificial Intelligence, vol. 69, nos. 1-2, pp. 279-305, November 1994.
13. M. Modrzejewski, "Feature selection using rough sets theory," in Proceedings of the European Conference on Machine Learning, edited by P.B. Brazdil, 1993, pp. 213-226.
14. H. Liu and W.X. Wen, "Concept learning through feature selection," in Proceedings of First Australian and New Zealand Conference on Intelligent Information Systems, 1993, pp. 293-297.
15. J.R. Quinlan, "Induction of decision trees," Machine Learning, vol. 1, no. 1, pp. 81-106, 1986.
16. G. Pagallo and D. Haussler, "Boolean feature discovery in empirical learning," Machine Learning, vol. 5, pp. 71-99, 1990.
17. J.R. Quinlan, C4.5: Programs for Machine Learning, Morgan Kaufmann, 1993.
18. H. Liu and R. Setiono, "A probabilistic approach to feature selection - a filter solution," in Proceedings of International Conference on Machine Learning (ICML-96), edited by L. Saitta, Morgan Kaufmann Publishers, 1996, pp. 319-327.
19. G. Brassard and P. Bratley, Fundamentals of Algorithms. Prentice Hall: NJ, 1996.
20. S. Watanabe, Pattern Recognition: Human and Mechanical, Wiley Interscience, 1985.
21. P. Mehra, L.A. Rendell, and B.W. Wah, "Principled constructive induction," in Proceedings of IJCAI, August 1989, pp. 651-656.
22. W.H. Press, S.A. Teukolsky, W.T. Vetterling, and B.P. Flannery, Numerical Recipes in C, Cambridge University Press: Cambridge, 1992.
23. T.W. Rauber, "Inductive pattern classification methods - features-sensors," Ph.D. Thesis, Dept. of Electrical Engineering, Universidade Nova de Lisboa, Lisboa, 1994.
24. C.J. Merz and P.M. Murphy, "UCI repository of machine learning databases," http://www.ics.uci.edu/~mlearn/ MLRepository.html. Irvine, CA: University of California, Department of Information and Computer Science, 1996.
25. S.B. Thrun et al., "The Monk's problems: A performance comparison of different learning algorithms," Technical Report CMU-CS-91-197, Carnegie Mellon University, 1991.
26. Sholom M. Weiss and Casimir A. Kulikowski, Computer Systems That Learn, Morgan Kaufmann Publishers: San Mateo, CA, 1991.
27. M. Boddy and T.L. Dean, "Deliberation scheduling for problem solving in time-constrained environments," Artificial Intelligence, vol. 67, no. 2, pp. 245-285, 1994.
28. H. Liu and R. Setiono, "Feature selection and classification - a probabilistic wrapper approach," in Proceedings of the Ninth International Conference on Industrial and Engineering Applications of AI and ES, 1996, pp. 419-424.
29. R. Kohavi, "Wrappers for performance enhancement and oblivious decision graphs," Ph.D. Thesis, Department of Computer Science, Standford University, Stanford, CA, 1995.
30. H. Liu and R. Setiono, "Chi2: Feature selection and discretization of numeric attributes," in Proceedings of the Seventh IEEE International Conference on Tools with Artificial Intelligence, 1995, pp. 388-391.