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March 1978 (vol. 27 no. 3)
pp. 261-266
| ASCII Text | x | ||
| J. Fehlauer, B.A. Eisenstein, "A Declustering Criterion for Feature Extraction in Pattern Recognition," IEEE Transactions on Computers, vol. 27, no. 3, pp. 261-266, March, 1978. | |||
| BibTex | x | ||
| @article{ 10.1109/TC.1978.1675083, author = {J. Fehlauer and B.A. Eisenstein}, title = {A Declustering Criterion for Feature Extraction in Pattern Recognition}, journal ={IEEE Transactions on Computers}, volume = {27}, number = {3}, issn = {0018-9340}, year = {1978}, pages = {261-266}, doi = {http://doi.ieeecomputersociety.org/10.1109/TC.1978.1675083}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, } | |||
| RefWorks Procite/RefMan/Endnote | x | ||
| TY - JOUR JO - IEEE Transactions on Computers TI - A Declustering Criterion for Feature Extraction in Pattern Recognition IS - 3 SN - 0018-9340 SP261 EP266 EPD - 261-266 A1 - J. Fehlauer, A1 - B.A. Eisenstein, PY - 1978 KW - Rayleigh quotients KW - Clustering KW - feature extraction KW - linear transformation KW - nonparametric classification KW - pattern recognition KW - principal component analysis VL - 27 JA - IEEE Transactions on Computers ER - | |||
A feature extraction technique based on a new criterion for "declustering" is presented. Declustering occurs when sample vectors from one pattern class form a densely packed point constellation, or cluster, in feature space while vectors from another class do not form a cluster but instead array themselves as outliers. Features chosen to optimize the declustering criterion enhance class separation and are robust over a wide range of measurement statistics.
Index Terms:
Rayleigh quotients, Clustering, feature extraction, linear transformation, nonparametric classification, pattern recognition, principal component analysis
Citation:
J. Fehlauer, B.A. Eisenstein, "A Declustering Criterion for Feature Extraction in Pattern Recognition," IEEE Transactions on Computers, vol. 27, no. 3, pp. 261-266, March 1978, doi:10.1109/TC.1978.1675083
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