Genetic design of feature spaces for pattern classifiers

Artificial Intelligence in Medicine

Volumn 32, Issue 2, 2004, Pages 115-125

  Pedrycz, Witold ^a   Breuer, Arnon ^a   Pizzi, Nicolino J ^b  

^a UNIVERSITY OF ALBERTA   (Canada)

^b NATIONAL RESEARCH COUNCIL CANADA   (Canada)

Author keywords

Curve fitting; Feature formation and reduction; Genetic algorithms; Pattern classification

Indexed keywords

APPROXIMATION THEORY; DATA ACQUISITION; FUNCTIONS; GENETIC ALGORITHMS; GENETIC ENGINEERING; PATTERN RECOGNITION; POLYNOMIALS; VECTORS;

BIOMEDICAL SPECTRAL DATA; GENETIC DESIGNS; PIECEWISE LINEAR APPROXIMATIONS;

ARTIFICIAL INTELLIGENCE;

ANALYTIC METHOD; ANALYTICAL PARAMETERS; ARTICLE; BIOMEDICINE; CHROMOSOME STRUCTURE; GENETIC ALGORITHM; INTERMETHOD COMPARISON; LINEAR SYSTEM; PRINCIPAL COMPONENT ANALYSIS; PRIORITY JOURNAL; SPECTROSCOPY;

ALGORITHMS; DATA INTERPRETATION, STATISTICAL; GENETICS; HUMANS; MEDICAL INFORMATICS;

EID: 4444338034     PISSN: 09333657     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.artmed.2004.01.005     Document Type: Article

References (26)

1. Bellman R. Adaptive control processes: a guided tour. Princeton: Princeton University Press, 1961.
2. Bishop CM. Neural networks for pattern recognition. Oxford: Oxford University Press, 1995.
3. Duda RO, Hart PE, Stork DG. Pattern classification. 2nd ed. New York: Wiley, 2001.
4. Mortimer R.K., Contopoulou C.R., King J.S. Genetic and physical maps of Saccharomyces cerevisiae. Yeast. 8:1992;817-902
5. Friebolin H. Basic one- and two-dimensional NMR spectroscopy. 3rd ed. New York: Wiley, 1998.
6. Pizzi N.J. Fuzzy preprocessing of gold standards as applied to biomedical spectra classification. Artif. Intell. Med. 16:1999;171-182
7. Himmelreich U, Somorjai RL, Dolenko B, Lee OC, Daniel H-M, Mountford CE, et al. Rapid Identification of Candida Species Using Nuclear Magnetic Resonance Spectroscopy and a Statistical Classification Strategy. Appl Environ Microbiol 2003;69:4566-74.
8. Keogh E, Chu S, Hart D, Pazzani M. An online algorithm for segmenting time series. In: Proceedings of the IEEE International Conference on Data Mining, 2001. p. 289-96.
9. Nygaard R, Husøy JH, Haugland D, Aase SO. Signal compression by piecewise linear non-interpolating approximation. In: Proceedings of the International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Phoenix, AZ, USA, March 1999. p. 1273-6.
10. Dipersio DA, Barr RC. Evaluation of the fan method of adaptive sampling on human electrocardiograms. Medical & Biological Engineering & Computing, September 1985. p. 401-10.
11. Imai H., Iri M. An optimal algorithm for approximating a piecewise linear function. J. Inform. Process. 9(3):1986;59-62
12. Douglas D., Peuker T. Algorithms for the reduction of the number of points required to represent a digitised line or its caricature. Can. Cartogr. 10:1973;112-122
13. Duda RO, Hart PE. Pattern classification and scene analysis. New York: Wiley, 1973.
14. Heckbert PS, Garland M. Survey of polygonal surface simplification algorithms. In: Proceedings of the SIGGRAPH'97, Multiresolution Surface Modeling Course Notes, 1997.
15. Hershberger J, Snoeyink J. Speeding up the Douglas-Peucker line-simplification algorithm. In: Proceedings of the Fifth Symposium on Data Handling, 1992. p. 134-43.
16. White E.R. Assessment of line-generalization algorithms using characteristic points. Am. Cartogr. 12(1):1985;17-27
17. E. Keogh, http://www.cs.ucr.edu/~eamonn/TSDMA/time_series_toolbox/.
18. Beasley D., Bull D.R., Martin R.R. An overview of genetic algorithms. Part 1. Fundamentals. Univ. Comput. 15(2):1993;58-69
19. Chambers L. The practical handbook of genetic algorithms. 2nd ed. London/Boca Raton, FL: Chapman & Hall/CRC Press, 2001.
20. Goldberg DE. Genetic algorithms in search, optimization and machine learning. Reading, MA: Addison-Wesley, 1989.
21. Holland JH. Adaptation in natural and artificial systems. Ann Arbor, MI: University of Michigan Press, 1975.
22. Michalewicz Z. Genetic algorithms+data structures=evolutionary programs. Berlin, Germany: Springer-Verlag, 1992.
23. Herrera F., Lozano M., Verdegay J.L. Tackling real-coded genetic algorithms: operators and tools for behavioral analysis. Artif. Intell. Rev. 12:1998;265-319
24. Pittman J., Murthy C.A. Fitting optimal piecewise linear functions using genetic algorithms. IEEE Pattern Anal. Mach. Intell. 22(7):2000;701-718
25. Pittman J, Murthy CA. Optimal line fitting using genetic algorithms. Technical Report 99-02. Department of Statistics, The Pennsylvania State University, University Park, July 1997.
26. Gacek A, Pedrycz W. A genetic segmentation of ECG signals. IEEE Trans Biomed Eng 2003;50(10):1203-8.