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Nonparametric density prediction for adaptation decision rule in the bayesian approach to the pattern recognition

Keywords:

M.A. Mitrohin – Ph. D. (Eng.) S.M. Zaharov – Ph. D. (Eng.)


A method for predicting of empirical density function on the basis of quantile regression and possibility of its use for decision rules adaptation in Bayesian approach to the pattern recognition.
References:

 

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  2. Panin O.A. Obnaruzhenie narushitelja tekhnicheskimi sredstvami: kriterii kachestva i sintez algoritmov // Specialnaja tekhnika. 2004. № 1.
  3. Parzen, Emanuel. On Estimation of a Probability Density Function and Mode // The Annals of Mathematical Statistics. 1962. V. 33. № 3. P. 1065−1076; Rosenblatt, Murray. Remarks on Some Nonparametric Estimates of a Density Function // The Annals of Mathematical Statistics. 1956. V. 27. № 3. P. 832−837.
  4. Fisher R.A. On the probable error of a coefficient of correlation deduced from a small sample // Metron. 1921. № 1. P. 1−32; On the mathematical foundations of theoretical statistics // Philosophical Transactions of the Royal Society. 1922. A 222. P. 309−368.
  5. Zvezhinskijj S.S. Problema vybora perimetrovykh sredstv obnaruzhenija // BDI. 2002. № 4. S. 36−41. № 5. S. 35−40.

 

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