ON THE MINIMIZATION OF CLASSIFICATION ERROR PROBABILITY IN STATISTICAL PATTERN RECOGNITION.

J. Fritz, L. Györfi

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

A two class pattern recognition algorithm is introduced for learning the optimal separating function within a given finite dimensional linear space of functions. It is proved that the algorithm converges with probability one to the separating function minimizing the probability of misclassification over the given class. This stochastic gradient process is based on asymptotically unbiased estimates of the gradient vector of error probability. This method is proposed. to improve classification rules obtained by other methods.

Original languageEnglish
Title of host publicationProbl Control Inf Theory
Pages371-382
Number of pages12
Volume5
Edition4
Publication statusPublished - 1976

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Pattern recognition
Error probability

ASJC Scopus subject areas

  • Engineering(all)

Cite this

Fritz, J., & Györfi, L. (1976). ON THE MINIMIZATION OF CLASSIFICATION ERROR PROBABILITY IN STATISTICAL PATTERN RECOGNITION. In Probl Control Inf Theory (4 ed., Vol. 5, pp. 371-382)

ON THE MINIMIZATION OF CLASSIFICATION ERROR PROBABILITY IN STATISTICAL PATTERN RECOGNITION. / Fritz, J.; Györfi, L.

Probl Control Inf Theory. Vol. 5 4. ed. 1976. p. 371-382.

Research output: Chapter in Book/Report/Conference proceedingChapter

Fritz, J & Györfi, L 1976, ON THE MINIMIZATION OF CLASSIFICATION ERROR PROBABILITY IN STATISTICAL PATTERN RECOGNITION. in Probl Control Inf Theory. 4 edn, vol. 5, pp. 371-382.
Fritz J, Györfi L. ON THE MINIMIZATION OF CLASSIFICATION ERROR PROBABILITY IN STATISTICAL PATTERN RECOGNITION. In Probl Control Inf Theory. 4 ed. Vol. 5. 1976. p. 371-382
Fritz, J. ; Györfi, L. / ON THE MINIMIZATION OF CLASSIFICATION ERROR PROBABILITY IN STATISTICAL PATTERN RECOGNITION. Probl Control Inf Theory. Vol. 5 4. ed. 1976. pp. 371-382
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