Inscrição na biblioteca: Guest
Portal Digital Begell Biblioteca digital da Begell eBooks Diários Referências e Anais Coleções de pesquisa
Journal of Automation and Information Sciences
SJR: 0.238 SNIP: 0.464 CiteScore™: 0.27

ISSN Imprimir: 1064-2315
ISSN On-line: 2163-9337

Volumes:
Volume 51, 2019 Volume 50, 2018 Volume 49, 2017 Volume 48, 2016 Volume 47, 2015 Volume 46, 2014 Volume 45, 2013 Volume 44, 2012 Volume 43, 2011 Volume 42, 2010 Volume 41, 2009 Volume 40, 2008 Volume 39, 2007 Volume 38, 2006 Volume 37, 2005 Volume 36, 2004 Volume 35, 2003 Volume 34, 2002 Volume 33, 2001 Volume 32, 2000 Volume 31, 1999 Volume 30, 1998 Volume 29, 1997 Volume 28, 1996

Journal of Automation and Information Sciences

DOI: 10.1615/JAutomatInfScien.v47.i10.60
pages 60-68

Application of Smoothing Measures in Nonparametric Kernel Classifiers with Usage of Normal Approximation of Probabilities

Alexander A. Galkin
Kiev National Taras Shevchenko University, Kiev

RESUMO

The problem of selection of bandwidth with application of kernel estimates of density of distribution was investigated, where instead of one optimal bandwidth for every density estimate we used results of different measures of smoothing for kernel estimates of density. We propose approach, where instead of unprocessed experimental relations normal approximations of the corresponding probabilities is used, and asymptotic properties were investigated for the corresponding conditions of regularity.

Referências

  1. Vardi Y., Zhang C.H. , The multivariate on <i>L</i><sub>1</sub>-median and associated data depth, Proc. of the National Academy of Sciences (USA), 2000, No. 97, 1423-1426.

  2. Godtliebsen F., Marron J.S., Chaudhuri P., Significance in scale space for bivariate density estimation. Journal of Computational and Graphical Statistics, 2002, No. 11, 1-22.

  3. Holmes C.C., Adams N.M., A probabilistic nearest neighbor method for statistical pattern recognition, Journal of the Royal Statistical Society, 2002, No. 64, 295-306.

  4. Hall P. , Large sample optimality of least squares cross validations in density estimation, The Annals of Statistics, 1983, No. 11, 1156-1174.

  5. Zuo Y., Serfling R., Structural properties and convergence results for contours of sample statistical depth functions, Ibid., 2000, No. 28, 483-499.

  6. Mosler K., Multivariate dispersions, central regions and depth, Springer-Verlag, New York, 2002, 1-14.

  7. Lachenbruch P., Mickey M., Estimation of error rates in discriminant analysis, Technometrics, 1968, No. 10, 1-11.

  8. Silverman B.W., Density estimation for statistics and data analysis, Chapman and Hall, London, 1986, 1-7.


Articles with similar content:

METHODOLOGY FOR MODEL DISCRIMINATION AND CRITICISM FOR LIQUID ATOMIZATION DATA
Atomization and Sprays, Vol.8, 1998, issue 4
Rolf D. Reitz, Donald W. Stanton, Calvin C. Hung, Christopher J. Rutland, Peter K. Senecal
REVERSE COMPUTATION OF FORCED CONVECTION HEAT TRANSFER USING ADJOINT FORMULATION
ICHMT DIGITAL LIBRARY ONLINE, Vol.4, 2001, issue
Kazunari Momose, Hideo Kimoto
Growth of Secondary Bubbles on the Wall of a Primary Bubble in Superheated Liquid
Heat Transfer Research, Vol.34, 2003, issue 1&2
V. V. Guguchkin, Natalya Nikolaevna Avakimyan, A. S. Trofimov, N. I. Vasil'ev
IMPROVEMENT OF FLOW-ORIENTED FAST REROUTE MODEL BASED ON SCALABLE PROTECTION SOLUTIONS FOR TELECOMMUNICATION NETWORK ELEMENTS
Telecommunications and Radio Engineering, Vol.76, 2017, issue 6
O. S. Yeremenko, N. Tariki, A. V. Lemeshko
Theoretical and Methodical Principles of Capital Structure Management in the Innovation Activity of Telecommunication Operators
Journal of Automation and Information Sciences, Vol.50, 2018, issue 3
Kseniya V. Kovtunenko , Yuriy V. Kovtunenko , Ekaterina A. Tanashchuk