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pro vyhledávání: '"Jacek Koronacki"'
Autor:
Michał Dramiński, Jacek Koronacki
Publikováno v:
Journal of Statistical Software, Vol 85, Iss 1, Pp 1-28 (2018)
We describe the R package rmcfs that implements an algorithm for ranking features from high dimensional data according to their importance for a given supervised classification task. The ranking is performed prior to addressing the classification tas
Externí odkaz:
https://doaj.org/article/a8b7e3f9c1cb486bbf56e034eeaf995e
Autor:
Jacek Koronacki, Jan Ćwik
Publikováno v:
Neural Computing & Applications. 6:173-185
This paper is a continuation of the authors' earlier work [1], where a version of the Traven's [2] Gaussian clustering neural network (being a recursive counterpart of the EM algorithm) has been investigated. A comparative simulation study of the Gau
Autor:
Jacek Koronacki, U. Luboińska
Publikováno v:
Computational Statistics & Data Analysis. 18:317-330
Let X (1) ,..., X (m) be m independent, real-valued random variables with unknown densities and let Y = Ψ(X (1) ,...,X (m) ) be their known functional. The aim is to estimate the density of the random variable Y , given n independent realizations of
Autor:
Jacek Koronacki, W. Feluch
Publikováno v:
Computational Statistics & Data Analysis. 13:143-151
In the note, a simple modification of the least-squares cross-validation criterion is proposed for choosing the bandwidth of kernel density estimators. For an i.i.d. sample X1, X2, …, Xn, the modification consists in leaving out a number of terms w
Publikováno v:
Rough Sets and Current Trends in Computing ISBN: 9783540476931
RSCTC
RSCTC
A new method for estimation of attributes’ importance for supervised classification, based on the random forest approach, is presented. Essentially, an iterative scheme is applied, with each step consisting of several runs of the random forest prog
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::af865a6c2a6651e33f04c5cbbfc48603
https://doi.org/10.1007/11908029_58
https://doi.org/10.1007/11908029_58
Autor:
Jacek Koronacki, J. Cwik
Publikováno v:
Rough Sets and Current Trends in Computing ISBN: 9783540646556
Rough Sets and Current Trends in Computing
Rough Sets and Current Trends in Computing
A heuristic method of model choice for a nonlinear regression problem on real line, based on the Equation Finder (EF) of Zembowicz and Żytkow (1992), is proposed and discussed. In our implementations of the EF we use a new, actually a three-stage, p
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::12d956e6de677dcd03bd51f5bda060ca
https://doi.org/10.1007/3-540-69115-4_10
https://doi.org/10.1007/3-540-69115-4_10
Autor:
Jacek Koronacki
Publikováno v:
Banach Center Publications. 6:183-187