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Weighted Parzen Windows for Pattern Classification
May 1996 (vol. 18 no. 5)
pp. 567-570

Abstract—This correspondence introduces the weighted-Parzen-window classifier. The proposed technique uses a clustering procedure to find a set of reference vectors and weights which are used to approximate the Parzen-window (kernel-estimator) classifier. The weighted-Parzen-window classifier requires less computation and storage than the full Parzen-window classifier. Experimental results showed that significant savings could be achieved with only minimal, if any, error rate degradation for synthetic and real data sets.

[1] M.R. Anderberg, Cluster Analysis for Applications.New York: Academic Press, 1973.
[2] R.O. Duda and P.E. Hart, Pattern Classification and Scene Analysis.New York: John Wiley&Sons, 1973.
[3] R.A. Fisher, "The use of multiple measurements in taxonomic problems," Annals of Eugenics, vol. 7, pp. 179-188, 1936.
[4] J. Fan and J.S. Marron, "Fast implementation of nonparametric curve estimators," J. Computational and Graphical Statistics, vol. 3, no. 1, pp. 35-56, 1994.
[5] K. Fukunaga, Introduction to Statistical Pattern Recognition, second edition. Academic Press, 1990.
[6] A.K. Jain and M.D. Ramaswami, "Classifier design with Parzen windows," Pattern Recognition and Artificial Intelligence, pp. 211-228, E.S. Gelsema and L.N. Kanal, eds. North-Holland: Elsevier Science Publishers B.V., 1988.
[7] E. Parzen, "On estimation of a probability density function and mode," Ann. Math. Statistics, vol. 33, pp. 1,065-1,076, Sept. 1962.
[8] M. West, "Approximating posterior distributions by mixtures," J. Royal Statistical Soc. B, vol. 55, no. 2, pp. 409-422, 1993.

Index Terms:
Nonparametric classifiers, Parzen-windows, kernel estimator, clustering, training samples, discriminant analysis, Bayes error, leave-one-out, holdout.
Gregory A. Babich, Octavia I. Camps, "Weighted Parzen Windows for Pattern Classification," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 18, no. 5, pp. 567-570, May 1996, doi:10.1109/34.494647
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