Estimation of Classification Error | IEEE Journals & Magazine | IEEE Xplore

Estimation of Classification Error


Abstract:

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...Show More

Abstract:

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.
Published in: IEEE Transactions on Computers ( Volume: C-20, Issue: 12, December 1971)
Page(s): 1521 - 1527
Date of Publication: 14 August 2006

ISSN Information:


Contact IEEE to Subscribe

References

References is not available for this document.