Evaluation of a modified Parzen classifier in high dimensional spaces

Proceedings - International Conference on Pattern Recognition

Volumn 15, Issue 2, 2000, Pages 67-70

  Muto, Yoshihiko ^a   Nagase, Hirokazu ^b   Hamamoto, Yoshihiko ^b  

^a UBE NATIONAL COLLEGE OF TECHNOLOGY   (Japan)

^b YAMAGUCHI UNIVERSITY   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

STATISTICAL METHODS;

BOOTSTRAP TECHNIQUE; CURSE OF DIMENSIONALITY; HIGH DIMENSIONAL SPACES; NON-PARAMETRIC; TOEPLITZ;

PATTERN RECOGNITION;

EID: 0012435553     PISSN: 10514651     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Article

References (6)

1. K. Fukunaga. Introduction to Statistical Pattern Recognition, 2nd edition. Academic Press, New York, 1990.
2. Y. Hamamoto, Y. Fujimoto, and S. Tomita. On the estimation of a covariance matrix in designing Parzen classifiers. Pattern Recognition, 29(10):1751-1759, October 1996.
3. Y. Hamamoto, S. Uchimura, and S. Tomita. A bootstrap technique for nearest neighbor classifier design. IEEE Trans. PAMI, 19(1):73-79, January 1997.
4. A. K. Jain and M. D. Ramaswami. Classifier design with Parzen windows. In E. S. Gelsema and L. N. Kanal, editors, Pattern Recognition and Artificial Intelligence, pages 211-228. Elsevier Science Publishers E.V., North-Holland, 1988.
5. J. V. Ness. On the dominance of non-parametric Bayes rule discriminant algorithms in high dimensions. Pattern Recognition, 12:355-368, December 1980.
6. S. J. Raudys and A. K. Jain. Small sample size effects in statistical pattern recognition: Recommendations for practitioners. IEEE Trans. PAMI, 13(3):252-264, March 1991.