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Issue No.12 - December (1993 vol.15)
pp: 1326-1330
ABSTRACT
<p>An effective data reduction technique based on vector quantization is introduced for nonparametric classifier design. Two new nonparametric classifiers are developed, and their performance is evaluated using various examples. The new methods maintain a classification accuracy that is competitive with that of classical methods but, at the same time, yields very high data reduction rates.</p>
INDEX TERMS
vector quantization; nonparametric classifier; design; k-nearest neighbour; data reduction rates; Parzen kernel classifier; condensing algorithm; approximation theory; data reduction; pattern recognition; vector quantisation
CITATION
Q. Xie, C.A. Laszlo, R.K. Ward, "Vector Quantization Technique for Nonparametric Classifier Design", IEEE Transactions on Pattern Analysis & Machine Intelligence, vol.15, no. 12, pp. 1326-1330, December 1993, doi:10.1109/34.250849
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