Just-in-time adaptive classifiers - Part II: Designing the classifier

IEEE Transactions on Neural Networks

Volumn 19, Issue 12, 2008, Pages 2053-2064

  Alippi, Cesare ^a   Roveri, Manuel ^a  

^a POLITECNICO DI MILANO   (Italy)

Author keywords

Intelligent systems; Learning systems; Neural networks; Pattern classification

Indexed keywords

CLASSIFIERS; COMPUTATIONAL COMPLEXITY; DATA REDUCTION; INTELLIGENT CONTROL; INTELLIGENT SYSTEMS; JUST IN TIME PRODUCTION; KNOWLEDGE BASED SYSTEMS; NEURAL NETWORKS; TEXT PROCESSING;

ACCURACY IMPROVEMENTS; ADAPTIVE CLASSIFICATIONS; ADAPTIVE CLASSIFIERS; ADAPTIVE MANAGEMENTS; ADAPTIVE SOLUTIONS; AGING EFFECTS; CHANGING CONDITIONS; CLASSIFICATION SYSTEMS; ENVIRONMENTAL CHANGES; GENERAL FRAMEWORKS; JUST IN TIMES; K-NEAREST NEIGHBORS; KNOWLEDGE BASE; MODEL COMPLEXITIES; NN CLASSIFIERS; NON STATIONARIES; NONSTATIONARY ENVIRONMENTS; NOVEL INFORMATIONS; PATTERN CLASSIFICATION; PHYSICAL SYSTEMS; PROCESS CHANGES; PROCESS DEVIATIONS; PROCESS EVOLUTIONS; REAL APPLICATIONS; REDUCTION MECHANISMS; STATIONARY CONDITIONS; STATIONARY STATES; TEMPORAL DETECTIONS; THERMAL DRIFTS;

LEARNING SYSTEMS;

ALGORITHM; ARTICLE; ARTIFICIAL NEURAL NETWORK; AUTOMATED PATTERN RECOGNITION; COMPUTER SIMULATION; METHODOLOGY; THEORETICAL MODEL;

ALGORITHMS; COMPUTER SIMULATION; MODELS, THEORETICAL; NEURAL NETWORKS (COMPUTER); PATTERN RECOGNITION, AUTOMATED;

EID: 57749121230     PISSN: 10459227     EISSN: None     Source Type: Journal    
DOI: 10.1109/TNN.2008.2003998     Document Type: Article

References (44)

1. K. Nozaki, H. Ishibuchi, and H. Tanaka, "Adaptive fuzzy rule-based classification systems," IEEE Trans. Fuzzy Syst., vol. 4, no. 3, pp. 238-250, Aug. 1996.
2. L. E. Doherty, "A computer based adaptive learning process," in Proc. Int. Conf. Knowl.-Based Intell. Electron. Syst., Zagreb, Croatia, 1998, vol. 3, pp. 303-306.
3. Q. Jackson and D. A. Landgrebe, "An adaptive classifier design for high-dimensional data analysis with a limited training data set," IEEE Trans. Geosci. Remote Sens., vol. 39, no. 12, pp. 2664-2679, Dec. 2001.
4. M. M. Rizki, M. A. Zmuda, and L. A. Tamburino, "Evolving pattern recognition systems," IEEE Trans. Evolut. Comput., vol. 6, no. 6, pp. 594-609, Dec. 2002.
5. N. Iwayama, K. Akiyama, and K. Ishigaki, "Hybrid adaptation: Integration of adaptive classification with adaptive context processing," in Proc. Int. Workshop Frontiers Handwriting Recognit. Aug. 2002, pp. 169-174.
6. N. Kasabov, "Evolving connectionist systems for adaptive learning and knowledge discovery: Methods, tools, applications," in Proc. Int. Conf. Neural Inf. Process., Singapore, Nov. 2002, vol. 2, pp. 590-595.
7. M. R. Azimi-Sadjadi, D. Yao, A. A. Jamshidi, and G. J. Dobeck, "Underwater target classification in changing environments using an adaptive feature mapping," IEEE Trans. Neural Netw., vol. 13, no. 5, pp. 1099-1111, Sep. 2002.
8. J.Wang, M. R. Azimi-Sadjadi, and D. Reinke, "A temporally adaptive classifier for multispectral imagery," IEEE Trans. Neural Netw., vol. 15, no. 1, pp. 159-165, Jan. 2004.
9. F. Virili and B. Freisleben, "Nonstationarity and data preprocessing for neural network predictions of an economic time series," in Proc. IEEE Int. Joint Conf. Neural Netw., Como, Italy, Jul. 2000, vol. 5, pp. 129-134.
10. P. Li, W. Melvin, M. Wicks, P. Antonik, and H. Schuman, "Knowledge-based space-time adaptive processing," in Proc. IEEE Nat. Radar Conf., Syracuse, NY, 1997, pp. 372-377.
11. H. Shah-Hosseini and R. Safabakhsh, "Pattern classification by the time adaptive self-organizing map," in Proc. IEEE Int. Conf. Electron. Circuits Syst., Jounieh, Lebanon, Dec. 2000, vol. 1, pp. 495-498.
12. G. A. Carpenter, S. Grossberg, and J. H. Reynolds, "A fuzzy artmap nonparametric probability estimator for nonstationary pattern recognition problems," IEEE Trans. Neural Netw., vol. 6, no. 6, pp. 1330-1336, Nov. 1995.
13. L. Rutkowski, "Adaptive probabilistic neural networks for pattern classification in time-varying environment," IEEE Trans. Neural Netw., vol. 15, no. 4, pp. 811-827, Jul. 2004.
14. A. Kuh, "Performance of analog neural networks subject to drifting targets and noise," in Proc. IEEE Int. Joint Conf. Neural Netw., Washington, DC, Jul. 1999, vol. 4, pp. 2406-2409.
15. A. Kuh, "Comparison of tracking algorithms for single layer threshold networks in the presence of random drift," IEEE Trans. Signal Process., vol. 45, no. 3, pp. 640-649, Mar. 1997.
16. M. A. Elbestawi, N. K. Sinha, R. Lingarkar, and L. Liu, "Knowledge-based adaptive computer control in manufacturing systems: A case study," IEEE Trans. Syst. Man Cybern., vol. 20, no. 3, pp. 606-618, May/Jun. 1990.
17. W. H. Land, L. Albertelli, Y. Titkov, P. Kaltsatis, and G. Seburyano, "Evolution of neural networks for the detection of breast cancer," in Proc. IEEE Int. Joint Symp. Intell. Syst., Rockville, MD, 1998, pp. 34-40.
18. P. Robertson and J. M. Brady, "Adaptive image analysis for aerial surveillance," IEEE Intell. Syst. Their Appl., vol. 14, no. 3, pp. 30-36, May-Jun. 1999.
19. S. C. Tan and C. P. Lim, "Condition monitoring and fault prediction via an adaptive neural network," in Proc. TENCON, Kuala Lumpur, Malaysia, Sep. 2000, vol. 1, pp. 13-17.
20. T. E. Boult, R. J. Micheals, X. Gao, and M. Eckmann, "Into the woods: Visual surveillance of noncooperative and camouflaged targets in complex outdoor settings," Proc. IEEE, vol. 89, no. 10, pp. 1382-1402, Oct. 2001.
21. A. Siddique, G. S. Yadava, and B. Singh, "Applications of artifcial intelligence techniques for induction machine stator fault diagnostics: Review," in Proc. IEEE Int. Symp. Diag. Electr. Mach. Power Electron. Drives, Stone Mountain, GA, Aug. 2003, pp. 29-34.
22. C. Alippi and M. Roveri, "Just-in-time adaptive classifiers - Part I: Detecting nonstationarity changes," IEEE Trans. Neural Netw., vol. 19, no. 7, pp. 1145-1143, Jul. 2008.
23. C. Alippi and P. Braione, "Classification methods and inductive learning rules: What we may learn from theory," IEEE Trans. Syst. Man Cybern., vol. 36, no. 5, pp. 649-655, Sep. 2006.
24. H. Chernoff, Sequential Analysis and Optimal Design. Philadelphia, PA: SIAM, 1972.
25. T. M. Cover and R. E. Hart, "Nearest neighbor pattern classification," IEEE Trans. Inf. Theory, vol. 13, no. 1, pp. 21-27, Jan. 1967.
26. K. Fukunaga, Introduction to Statistical Pattern Recognition. New York: Academic, 1972.
27. C. Stone, "Consistent nonparametric regression," Ann. Statist., vol. 8, pp. 1348-1360, 1977.
28. K. Fukunaga and L. Hostetler, "Optimization of k nearest neighbor density estimates," IEEE Trans. Inf. Theory, vol. 19, no. 3, pp. 320-326, May 1973.
29. L. Devroye, L. Gyorfi, and G. Lugosi, A Probabilistic Theory of Pattern Recognition. New York: Springer-Verlag, 1996.
30. P. A. Lachenbruch and M. R. Mickey, "Estimation of error rates in discriminant analysis," Technometrics, vol. 10, pp. 1-10, 1968.
31. M. Keans and D. Ron, "Algorithmic stability and sanity check bounds for leave-one-out cross validation bounds," Neural Comput., vol. 11, no. 6, pp. 1427-1453, 1999.
32. L. P. Devroye and T. J. Wagner, "Distribution-free inequalities for the deleted and holdout error estimates," IEEE Trans. Inf. Theory, vol. 25, no. 5, pp. 601-604, Sep. 1979.
33. P. E. Hart, "The condensed nearest neighbor rule," IEEE Trans. Inf. Theory, vol. 14, no. 3, pp. 515-516, May 1968.
34. G. W. Gates, "The reduced nearest neighbor rule," IEEE Trans. Inf. Theory, vol. 18, no. 3, pp. 431-433, May 1972.
35. D. Wilson, "Asymptotic properties of nearest neighbor rules using edited data," IEEE Trans. Syst. Man Cybern., vol. 2, no. 3, pp. 408-421, Jul. 1972.
36. R. S. Poulsen, B. K. Bhattacharya, and G. T. Toussaint, "Application of proximity graphs to editing nearest neighbor decision rule," in Proc. Int. Symp. Inf. Theory, Santa Monica, CA, 1981, pp. 1-25.
37. C. Zonghai, Z. Haitao, L. Ming, and X. Wei, "Adaptive control method for nonlinear time-delay processes," J. Syst. Eng. Electron., vol. 18, pp. 566-576, 2007.
38. V. Hautamaki, I. Karkkainen, and P. Franti, "Outlier detection using k-nearest neighbour graph," in Proc. 17th Conf. Pattern Recognit. Cambridge, U.K., Aug. 2004, vol. 3, pp. 430-433.
39. E. L. Russel, L. H. Chiang, and R. D. Braatz, Fault Detection and Diagnosis in Industrial Systems. New York: Springer-Verlag, 2001.
40. I. V. Nikiforov, "A generalized change detection problem," IEEE Trans. Inf. Theory, vol. 41, no. 1, pp. 171-187, Jan. 1995.
41. C. Blake and C. Merz, UCI Machine Learning Databases Repository, Dept. Inf. Comput. Sci., Univ. California-Irvine [Online]. Available: http:// www.ics.uci.edu/~mlearn/databases/statlog/, Last accessed on: May 2008
42. M. Bollano, R. Piagge, A. Charai, and D. Narducci, "Experimental evidence and computational analysis of the electronic density modulation induced by gaseous molecules at Si(001) surfaces upon self-assembling organism monolayer," Appl. Surface Sci., vol. 175-176, pp. 379-385, 2001.
43. D. Narducci, P. Bernardiello, and M. Oldani, "Investigation of gassurface interactions at self-assembled silicon surfaces acting as gas sensor," Appl. Surface Sci., vol. 212-213, pp. 491-496, 2003.
44. J. Kohlmorgen, K.-R. Müller, J. Rittweger, and K. Pawelzik, "Identification of nonstationary dynamics in physiological recordings," Biol. Cybern., vol. 83, no. 1, pp. 73-84, 2000.