Abstract:
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 u...Show MoreMetadata
Abstract:
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.
Published in: IEEE Transactions on Pattern Analysis and Machine Intelligence ( Volume: 18, Issue: 5, May 1996)
DOI: 10.1109/34.494647