Feature extraction for one-class classification

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 2714, Issue , 2003, Pages 342-349

  Tax, David M J ^a   Müller, Klaus R ^a  

^a FRAUNHOFER FIRST   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

ECONOMIC AND SOCIAL EFFECTS; FEATURE EXTRACTION; NEURAL NETWORKS; PRINCIPAL COMPONENT ANALYSIS;

BIAS VARIANCE TRADE OFF; CLASSIFICATION TASKS; FEATURE REDUCTION; NOVELTY DETECTION; ONE-CLASS CLASSIFICATION;

CLASSIFICATION (OF INFORMATION);

EID: 35248863825     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-44989-2_41     Document Type: Article

References (15)

1. T.W. Anderson. An introduction to multivariate statistical analysis. John Wiley & Sons, 2nd edition, 1984.
2. Sung-Bae Cho. Recognition of unconstrained handwritten numerals by doubly self-organizing neural network. In International Cconference on Pattern Recognition, 1996.
3. S. Geman, E. Bienenstock, and R. Doursat. Neural networks and the bias/variance dilemma. Neural Computation, 4:1-58, 1992.
4. T. Heskes. Bias/variance decomposition for likelihood-based estimators. Neural Computation, 10:1425-1433, 1998.
5. J. Hardin and D.M. Rocke. The distribution of robust distances. Technical report, University of California at Davis, 1999.
6. B. Heisele, Poggio. T., and M. Pontil. Face detection in still gray images. A.I. memo 1687, Center for Biological and Computational Learning, MIT, Cambridge, MA, 2000.
7. N Japkowicz, C. Myers, and M. Gluck. A novelty detection approach to classification. In Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence, pages 518-523, 1995.
8. I.T. Jollife. Principal Component Analysis. Springer-Verlag, New York, 1986.
9. C.E. Metz. Basic principles of ROC analysis. Seminars in Nuclear Medicine, VIII(4), October 1978.
10. M.M. Moya and D.R. Hush. Network contraints and multi-objective optimization for one-class classification. Neural Networks, 9(3):463-474, 1996.
11. G. Ritter, M.T. Gallegos, and K. Gaggermeier. Automatic context-sensitive karyotyping of human elliptical symmetric statistical distributions. Pattern Recognition, 28(6):823-831, December 1995.
12. B Schölkopf, J. Platt, J. Shawe-Taylor, Smola A., and R. Williamson. Estimating the support of a high-dimensional distribution. Neural Computation, 13(7), 1999.
13. K.-K. Sung. Learning and Example Selection for Object and Pattern Recognition. PhD thesis, MIT, Artificial Intelligence Laboratory and Center for Biological and Computational Learning, Cambridge, MA, 1996.
14. D.M.J. Tax. One-class classification. PhD thesis, Delft University of Technology, http://www.ph.tn.tudelft.nl/~davidt/thesis.pdf, June 2001.
15. S. Wilks. Mathematical statistics. John Wiley, 1962.