Integrated sensing and processing decision trees

IEEE Transactions on Pattern Analysis and Machine Intelligence

Volumn 26, Issue 6, 2004, Pages 699-708

  Priebe, Carey E ^a   Marchette, David J ^b   Healy Jr , Dennis M ^c  

^a Johns Hopkins University   (United States)

^b NAVAL SURFACE WARFARE CENTER   (United States)

^c University of Maryland   (United States)

Author keywords

Adaptive sensing; Classification; Clustering; Local dimensionality reduction; Sequential sensing

Indexed keywords

ALGORITHMS; COMPUTER SIMULATION; FOURIER TRANSFORMS; IMAGE QUALITY; MAGNETIC RESONANCE IMAGING; OBJECT RECOGNITION; OPTIMIZATION; PATTERN RECOGNITION SYSTEMS; STATISTICAL METHODS;

CLUSTERING; INTEGRATED SENSING AND PROCESSING DECISION TREES; LOCAL DIMENSIONALITY REDUCTION; SEQUENTIAL SENSING;

DECISION THEORY;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; DECISION SUPPORT SYSTEM; METHODOLOGY; SYSTEM ANALYSIS;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; DECISION SUPPORT TECHNIQUES; PATTERN RECOGNITION, AUTOMATED; SYSTEMS INTEGRATION;

EID: 3042631931     PISSN: 01628828     EISSN: None     Source Type: Journal    
DOI: 10.1109/TPAMI.2004.12     Document Type: Article

References (21)

1. K. Abe and J. Jia, "Improvement of Decision Tree Generation by Using Instance-Based Learning and Clustering Method," Proc. IEEE Conf. Systems, Man, and Cybernetics, vo. 1, pp. 696-701, 1996.
2. R.E. Bellman, Adaptive Control Processes. Princeton, N.J.: Princeton Univ. Press, 1961.
3. L. Breiman, J.H. Friedman, R.A. Olshen, and C.J. Stone, Classification and Regression Trees. Boca Raton, Fla.: Chapman & Hall/CRC, 1998.
4. L. Breiman, "Random Forests, Random Features," Technical Report 567, Dept, of Statistics, Univ. of California, Berkeley, 1999.
5. T.A. Dickinson, J. White, J.S. Kauer, and D.R. Walt, "A Chemical-Detecting System Based on a Cross-Reactive Optical Sensor Array," Nature, vol. 382, pp. 697-700, 1996.
6. P.J. Green and B.W. Silverman, Nonparametric Regression and Generalized Linear Models: A Roughness Penalty Approach. Chapman and Hall, 1994.
7. J.A. Hartigan, Clustering Algorithms. New York: John Wiley & Sons, 1975.
8. T. Hastie and R. Tibshirani, "Discriminant Adaptive Nearest Neighbor Classification," IEEE Trans. Pattern Analysis and Machine Intelligence, vo. 18, pp. 607-616, 1996.
9. D.M. Healy Jr., D. Warner, and J.B. Weaver, "Applications of Adapted Wavelet Encoding in Functional Magnetic Resonance Imaging," Time-Frequency Methods in the Engineering and Biological Sciences, M. Akay, ed., New York: IEEE Press, 1997.
10. T.K. Ho, "The Random Subspace Method for Constructing Decision Forests," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 20, no. 8, pp. 832-844, Aug. 1998.
11. A.K. Jain, R.P.W. Duin, and J. Mao, "Statistical Pattern Recognition: A Review," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 22, no. 1, pp. 4-37, Jan. 2000.
12. Z.P. Liang and P.C. Lauterbur, Principles of Magnetic Resonance Imaging. New York: IEEE Press, 2000.
13. D.J. Marchette and W.L. Poston, "Local Dimensionality Reduction Using Normal Mixtures," Computational Statistics, vol. 14, pp. 469-489, 1999.
14. W. Pedrycz and Z.A. Sosnowski, "Designing Decision Trees with the Use of Fuzzy Granulation," IEEE Trans. Systems, Man, and Cybernetics, Part A: Systems and Humans, vol. 30, no. 2, pp. 151-159, 2000.
15. C.E. Priebe, "Olfactory Classification via Interpoint Distance Analysis," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 23, pp. 404-413, 2001.
16. C.E. Priebe, D.,J. Marchette, and D.M. Healy Jr., "Integrated Sensing and Processing for Statistical Pattern Recognition," Modern Signal Processing. D. Rockmore and D.M. Healy Jr., eds., Cambridge Univ. Press, 2004.
17. D.W. Scott, Multivariate Density Estimation: Theory, Practice, and Visualization. New York: John Wiley & Sons, 1992.
18. D.L. Swets and J. Weng, "Hierarchical Discriminant Analysis for Image Retrieval," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 21, pp. 386-401, 1999.
19. G.V. Trunk, "A Problem of Dimensionality: A Simple Example," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 1 , no. 3, pp. 306-307, 1979.
20. V.N. Vapnik, The Nature of Statistical Learning Theory. Springer, 1995.
21. J. White, J.S. Kauer, T.A. Dickinson, and D.R. Walt, "Rapid Analyte Recognition in a Device Based on Optical Sensors and the Olfactory System," Analytical Chemistry, vol. 68, pp. 2191-2202, 1996.