Classification of pyrolysis mass spectra by fuzzy multivariate rule induction-comparison with regression, K-nearest neighbour, neural and decision-tree methods

Analytica Chimica Acta

Volumn 348, Issue 1-3, 1997, Pages 389-407

  Alsberg, B K ^a   Goodacre, R ^a   Rowland, J J ^a   Kell, D B ^a  

^a ABERYSTWYTH UNIVERSITY   (United Kingdom)

Author keywords

Artificial neural networks; Canonical variate analysis; Classification and regression trees (CART); Discriminant partial least squares; Fuzzy rule building expert system (FuRES); K nearest neighbour method; PLS2; Pyrolysis mass spectrometry (PyMS); Rule induction

Indexed keywords

OLIVE OIL;

ALGORITHM; ARTIFICIAL NEURAL NETWORK; CALIBRATION; CONFERENCE PAPER; DECISION MAKING; EXPERT SYSTEM; FOOD ANALYSIS; FOOD QUALITY; INFORMATION PROCESSING; MASS SPECTROMETRY; PRIORITY JOURNAL; REGRESSION ANALYSIS; TECHNIQUE;

EID: 0030884306     PISSN: 00032670     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0003-2670(97)00064-0     Document Type: Conference Paper

References (79)

1. Y. Anzai, Pattern Recognition and Machine Learning, Academic Press, New York, 1989.
2. C.M. Bishop, Neural Networks for Pattern Recognition, Clarendon Press, Oxford, 1995.
3. R.G. Brereton, Multivariate Pattern Recognition in Chemometrics., Elsevier, Amsterdam, 1992.
4. K. Fukunaga, Introduction to Statistical Pattern Recognition, Academic Press, New York, 1992.
5. D. Helm, H. Labischinski and D. Naumann, J. Microbiological Methods, 14 (1991) 127-142.
6. G.J. McLachlan, Discriminant Analysis and Statistical Pattern Recognition, John Wiley, London, 1992.
7. G. Montague and J. Morris, Trends Biotechnol., 12 (1994) 312-324.
8. B.D. Ripley, Pattern Recognition and Neural Networks, Cambridge University Press, Cambridge, 1996.
9. R. Zamora, J.L. Navarro and F.J. Hidalgo, J. American Oil Chemists Soc., 71 (1994) 361-364.
10. D.B. Kell and B. Sonnleitner, Trends Biotechnol., 13 (1995) 481-492.
11. C.S. Gutteridge, L. Vallis and H.J.H. MacFie, in M. Goodfellow, D. Jones and F. Priest (Eds.), Computer-assisted Bacterial Systematics, Academic Press, London, 1985, pp. 369-401.
12. C.S. Gutteridge, Methods in Microbiology, 19 (1987) 227-272.
13. R. Goodacre, M.J. Neal and D.B. Kell, Anal. Chem., 66 (1994) 1070-1085.
14. R. Goodacre, M.J. Neal, D.B. Kell, L.W. Greenham, W.C. Noble and R.G. Harvey, J. Appl. Bacteriology, 76 (1994) 124-134.
15. H.L.C. Meuzelaar, J. Haverkamp and F.D. Hileman, Pyrolysis Mass Spectrometry of Recent and Fossil Biomaterials, Elsevier, Amsterdam, 1982.
16. W. Windig, H.L.C. Meuzelaar, B.A. Haws, W.F. Campbell and K.H. Asay, J. Anal. Appl. Pyrolysis, 5 (1983) 183-198.
17. W.J. Irwin, Analytical Pyrolysis: A Comprehensive Guide, Marcel Dekker, New York, 1982.
18. D. Coomans, D.L. Massart and L. Kaufman, Anal. Chim. Acta, 112 (1979) 97.
19. P.A. Lachenbruch, Discriminant Analysis, Haffner Press, New York, 1975.
20. S. Haykin, Neural Networks, Macmillan, New York, 1994.
21. R. Hecht-Nielsen, Neurocomputing, Addison-Wesley, Massachusetts, 1990.
22. J.M. Henle, An Outline of Set Theory, Springer-Verlag, New York, 1986.
23. L. Breiman, J.H. Friedman, R.A. Olshen and C.J. Stone, Classification and Regression Trees, Wadsworth, Pacific Grove, California, 1984.
24. P.d.B. Harrington and K.J. Voorhees, Anal. Chem., 62 (1990) 729-734.
25. J.R. Quinlan, Mach. Learning, 1 (1986) 81-106.
26. R. Goodacre, Applied Spectroscopy, in press.
27. R. Goodacre, D.B. Kell and G. Bianchi, Nature, 359 (1992) 594.
28. R. Goodacre, D.B. Kell and G. Bianchi, J. Science of Food and Agriculture, 63 (1993) 297-307.
29. R. Goodacre, S. Trew, C. Wrigley-Jones, G. Saunders, M.J. Neal, N. Porter and D.B. Kell, Anal. Chim. Acta, 313 (1995) 25-43.
30. B.F.J. Manly, Multivariate Statistical Methods: A Primer, Chapman and Hall, London, 1994.
31. W. Eshuis, P.G. Kistemaker and H.L.C. Meuzelaar, in C.E.R. Jones and C.A. Cramers (Eds.), Analytical Pyrolysis, Elsevier, Amsterdam, 1977, pp. 151-156.
32. J.B. Kruskal, Psychometrika, 29 (1964) 1-27.
33. J.B. Kruskal, Psychometrika, 29 (1964) 115-129.
34. C.E. Shannon, Bell System Technical J., 379(1948) 379-423, 623-656.
35. I.E.D. Minitab, State College, PA 16801-3008, SCAN Software for Chemometric Analysis, Release 1 for Windows ed., USA, 1995.
36. S.K. Murthy, S. Kasif and S. Salzberg, J. Artificial Intell. Research, 2 (1994) 1-32.
37. P.E. Utgoff and C.E. Brodley, Linear Machine Decision Trees, University of Massachusetts, Amherst, 1991.
38. B.A. Draper, C.E. Brodley and P.E. Utgoff, IEEE Tran. on Pattern Anal. and Machine Intell., 16(1994) 888-893.
39. C.E. Brodley and P.E. Utgoff, Mach. Learning, 19 (1995) 45-77.
40. L.A. Zadeh, Fuzzy sets, fuzzy logic, and fuzzy systems: Selected papers, World Scientific, River Edge, N.J., 1996.
41. P.d.B. Harrington, Chemometrics and Intell. Lab. Sys., 18 (1993) 157-170.
42. P.d.B. Harrington, J. Chemometrics, 5 (1991) 467-486.
43. J. Pannetier, Institute of Physics Conference Series, (1990) 23-44.
44. H.J.H. MacFie, C.S. Gutteridge and J.R. Norris, J. Gen. Microbiol., 104 (1978) 67-74.
45. J.A. Nelder, Genstat Reference Manual, Scientific and Social Service Program Library, University of Edinburgh, 1979.
46. D.E. Rumelhart, J.L. McClelland and The PDP Research Group, Parallel distributed processing, Experiments in the Microstructure of Cognition, MIT Press, Cambridge, 1986.
47. P.D. Wasserman, Neural Computing: Theory and Practice, Van Nostrand Reinhold, New York, 1989.
48. P.J. Werbos, The Roots of Back-propagation: From Ordered Derivatives to Neural Networks and Political Forecasting, John Wiley, Chichester, 1994.
49. J.C. Bezdek and S.K. Chuah, Fuzzy Sets and Sys., 18 (1986) 237-256.
50. D. Coomans and D.L. Massart, Anal. Chim. Acta, 138 (1982) 15.
51. J. Kittler and P.A. DeVijver, Pattern Recognition, 13 (1981) 245-249.
52. C. Schaffer, Mach. Learning, 13 (1993) 135-143.
53. S. Wold, N. Kettanehwold and B. Skagerberg, Chemometrics and Intell. Lab. Sys., 7 (1989) 53-65.
54. S. Wold, C. Albano, W.J. Dunn, K. Esbensen, S. Hellberg, E. Johansson, W. Lindberg and M. Sjostrom, Analusis, 12 (1984) 477-485.
55. S. Wold, A. Ruhe, H. Wold and W.J. Dunn, Siam J. Scientific and Statistical Computing, 5 (1984) 735-743.
56. S. Wold, Technometrics, 35 (1993) 136-139.
57. H. Martens and T. Næs, Multivariate Calibration, John Wiley, Chichester, 1989.
58. H. Martens, L. Izquierdo, M. Thomassen and M. Martens, Anal. Chim. Acta, 191 (1986) 133-148.
59. M. Martens, H. Martens and S. Wold, J. Science of Food and Agriculture, 34 (1983) 715-724.
60. R. Manne, Chemometrics and Intell. Lab. Sys., 2 (1987) 187-197.
61. A. Höskuldsson, J. Chemometrics, 6 (1992) 307-334.
62. A. Höskuldsson, J. Chemometrics, 9 (1995) 91-123.
63. T.R. Holcomb and M. Morari, Computers and Chem. Eng., 16 (1992) 393-411.
64. P. Geladi and B.R. Kowalski, Anal. Chim. Acta, 185 (1986) 1-17.
65. I.E. Frank, Chemometrics and Intell. Lab. Sys., 8 (1990) 109-119.
66. S. DeJong, J. Chemometrics, 9 (1995) 323-326.
67. S. DeJong, J. Chemometrics, 7 (1993) 551-557.
68. H. Martens and T. Naes, Multivariate Calibration, John Wiley and Sons, Chichester, 1989.
69. R. Andrews, J. Diederich and A.B. Tickle, Knowledge-based Syst., 8 (1995) 373-389.
70. S. Abe and M.S. Lan, IEEE Trans. Fuzzy Sys., 3 (1995) 18-28.
71. J. Downs, R.F. Harrison and S.S. Cross, Lecture Notes Artificial Intell., 934 (1995) 239-250.
72. D.L. Hudson, M.E. Cohen and M.F. Anderson, Int. J. Intell. Sys., 6 (1991) 213-223.
73. T. Ichimura, E. Tazaki and K. Yoshida, Int. J. Bio-Medical Computing, 40 (1995) 139-146.
74. H. Narazaki, T. Watanabe and M. Yamamoto, Ieee Trans. Systems Man and Cybernet. Part B-Cybernet., 26 (1996) 107-117.
75. C.W. Omlin and C.L. Giles, IEEE Trans. Knowledge and Data Eng., 8 (1996) 183-188.
76. C.W. Omlin and C.L. Giles, Neural Networks, 9 (1996) 41-52.
77. R. Setiono, Artificial Intell. in Medicine, 8 (1996) 37-51.
78. H.L. Viktor and I. Cloete, Lecture Notes Computer Sci., 930 (1995) 611-618.
79. G.G. Towell and J.W. Shavlik, Mach. Learning, 13 (1993) 71-101.