Ga. Babich et Oi. Camps, WEIGHTED PARZEN WINDOWS FOR PATTERN-CLASSIFICATION, IEEE transactions on pattern analysis and machine intelligence, 18(5), 1996, pp. 567-570
This correspondence introduces the weighted-Parzen-window classifier.
The proposed technique uses a clustering procedure to find a set of re
ference Vectors and weights which are used to approximate the Parzen-w
indow (kernel-estimator) classifier. The weighted-Parzen-window classi
fier requires less computation and storage than the full Parzen-window
classifier. Experimental results showed that significant savings coul
d be achieved with only minimal, if any, error rate degradation for sy
nthetic and real data sets.