Vector quantization technique for nonparametric classifier design

TitleVector quantization technique for nonparametric classifier design
Publication TypeJournal Article
Year of Publication1993
AuthorsXie, Q., C. A. LASZLO, and R. K. Ward
JournalPattern Analysis and Machine Intelligence, IEEE Transactions on
Volume15
Pagination1326 -1330
Date Publisheddec.
ISSN0162-8828
Keywordsapproximation theory, condensing algorithm, data reduction, data reduction rates, design, k-nearest neighbour, nonparametric classifier, Parzen kernel classifier, Pattern Recognition, vector quantisation, vector quantization
Abstract

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

URLhttp://dx.doi.org/10.1109/34.250849
DOI10.1109/34.250849

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