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Nonparametric Data Reduction
January 1984 (vol. 6 no. 1)
pp. 115-118
K. Fukunaga, Department of Electrical Engineering, Purdue University, West Lafayette, IN 47907.
J. M. Mantock, Department of Electrical Engineering, Purdue University, West Lafayette, IN; Aerospace Corporation, Los Angeles, CA; Texas Instruments, Inc., Dallas, TX.
A nonparametric data reduction technique is proposed. Its goal is to select samples that are ``representative'' of the entire data set. The technique is iterative and is based on the use of a criterion function and nearest neighbor density estimates. Experiments are presented to demonstrate the algorithm.
Citation:
K. Fukunaga, J. M. Mantock, "Nonparametric Data Reduction," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 6, no. 1, pp. 115-118, Jan. 1984, doi:10.1109/TPAMI.1984.4767485
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