Polishing Blemishes: Issues in Data Correction

IEEE Intelligent Systems

Volumn 19, Issue 2, 2004, Pages 34-39

  Teng, Choh Man ^a  

^a INSTITUTE FOR HUMAN AND MACHINE COGNITION   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DATA CORRECTION METHOD; DATA QUALITY; ROBUST ALGORITHMS; SEMIAUTOMATED FLAGGING PROCESS;

ALGORITHMS; BANDWIDTH; DATA MINING; KNOWLEDGE BASED SYSTEMS; LEARNING SYSTEMS; LIGHT EMITTING DIODES; MAN MACHINE SYSTEMS; MATHEMATICAL MODELS; NOISE ABATEMENT; PROGRAM DOCUMENTATION; SIGNAL FILTERING AND PREDICTION; SPURIOUS SIGNAL NOISE;

DATABASE SYSTEMS;

EID: 2142819999     PISSN: 15411672     EISSN: None     Source Type: Journal    
DOI: 10.1109/MIS.2004.1274909     Document Type: Article

References (10)

1. C.M. Teng, “Correcting Noisy Data,” Proc. 16th Int'l Conf. Machine Learning, Morgan Kaufmann, 1999, pp. 239-248.
2. P. Clark and T. Niblett, “The CN2 Induction Algorithm,” Machine Learning, vol. 3, no. 4, 1989, pp. 261-283.
3. J.R. Quinlan, C4.5: Programs for Machine Learning, Morgan Kaufmann, 1993.
4. G.H. John, “Robust Decision Trees: Removing Outliers from Databases,” Proc. First Int'l Conf. Knowledge Discovery and Data Mining, AAAI Press, 1995, pp. 174-179.
5. C.E. Brodley and M.A. Friedl, “Identifying Mislabeled Training Data,” J. Artificial Intelligence Res., vol. 11, 1999, pp. 131-167.
6. D. Gamberger, N. Lavrac, and C. Groselj, “Experiments with Noise Filtering in a Med ical Domain,” Proc. 16th Int'l Conf. Machine Learning, Morgan Kaufmann, 1999, pp. 143-151.
7. P.J. Rousseeuw and A.M. Leroy, Robust Regression and Outlier Detection, John Wiley, 1987.
8. C.L. Blake and C.J. Merz, “UCI Repository of Machine Learning Databases,” Dept. of Infor mation and Computer Science, Univ. of California, Irvine, 1998, www.ics.uci.edu/~mlearn/MLRepository.html.
9. C.M. Teng, “Evaluating Noise Correction,” Proc. Sixth Pacific Rim Int'l Conf. Artificial Intelligence, Springer-Verlag, 2000, pp. 188-198.
10. C.M. Teng, “Applying Noise Handling Tech niques to Genomic Data: A Case Study,” Proc. Third IEEE Int'l Conf. Data Mining, IEEE CS Press, 2003, pp. 743-746.