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Estimation of Classification Error
December 1971 (vol. 20 no. 12)
pp. 1521-1527
This paper discusses methods of estimating the probability of error for the Bayes' classifier which must be designed and tested with a finite number of classified samples. The expected difference between estimates is discussed. A simplifled algorithm to compute the leaving-one-out method is proposed for multivariate normal distributions wtih unequal co-variance matrices. The discussion is extended to nonparametric classifiers by using the Parzen approximation for the density functions. Experimental results are shown for both parametric and nonparametric cases.
Index Terms:
Bayes' classifier, estimation, finite number of samples, pattern recognition, probability of error.
Citation:
K. Fukunaga, D.L. Kessell, "Estimation of Classification Error," IEEE Transactions on Computers, vol. 20, no. 12, pp. 1521-1527, Dec. 1971, doi:10.1109/T-C.1971.223165
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