Title | Vector quantization technique for nonparametric classifier design |
Publication Type | Journal Article |
Year of Publication | 1993 |
Authors | Xie, Q., C. A. LASZLO, and R. K. Ward |
Journal | Pattern Analysis and Machine Intelligence, IEEE Transactions on |
Volume | 15 |
Pagination | 1326 -1330 |
Date Published | dec. |
ISSN | 0162-8828 |
Keywords | approximation 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 |
URL | http://dx.doi.org/10.1109/34.250849 |
DOI | 10.1109/34.250849 |