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Weighted Parzen windows for pattern classification

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2 Author(s)
Babich, G.A. ; Appl. Res. Lab., Pennsylvania State Univ., University Park, PA, USA ; Camps, O.I.

This paper 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

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Pattern Analysis and Machine Intelligence, IEEE Transactions on  (Volume:18 ,  Issue: 5 )