Zobrazeno 1 - 10
of 22
pro vyhledávání: '"Yulia A. Zhuk"'
Publikováno v:
Naučno-tehničeskij Vestnik Informacionnyh Tehnologij, Mehaniki i Optiki, Vol 21, Iss 1, Pp 135-142 (2021)
The subject of the research. The paper provides an overview of a flood forecasting problem in the Nenetsky region, Russia. The solution involves the use of the open source data on water level during the spring floods. Specifically, its collection, an
Externí odkaz:
https://doaj.org/article/541446c77d1d42d5b51edb925c4d2549
Autor:
Lev V. Utkin, Yulia A. Zhuk
Publikováno v:
Knowledge-Based Systems. 120:43-56
A modification of the well-known one-class classification support vector machine (OCC SVM) dealing with interval-valued or set-valued training data is proposed. Its main idea is to represent every interval of training data by a finite set of precise
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1257be07c44ad197ed51738fdd2f5b74
https://doi.org/10.1016/j.knosys.2016.12.022
https://doi.org/10.1016/j.knosys.2016.12.022
Autor:
Yulia A. Zhuk, Lev V. Utkin
Publikováno v:
Knowledge-Based Systems. 61:59-75
Robust classification models based on the ensemble methodology are proposed in the paper. The main feature of the models is that the precise vector of weights assigned for examples in the training set at each iteration of boosting is replaced by a lo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fe227fa2d8756d8308e6ceaff5db1ad3
https://doi.org/10.1016/j.knosys.2014.02.007
https://doi.org/10.1016/j.knosys.2014.02.007
Publikováno v:
European Journal of Technology and Design. 3:49-60
Most models of aggregating expert judgments assume that there is some precise probability distribution characterizing the system behavior and expert information allows us to compute parameters of this distribution. However, judgments elicited from ex
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::02653df9beb79e5b9cf933fa732c0c9f
https://doi.org/10.13187/ejtd.2014.3.49
https://doi.org/10.13187/ejtd.2014.3.49
Publikováno v:
European Journal of Technology and Design. 1:70-76
A new feature selection algorithm for solving classification problems is proposed. The algorithm exploits the ensemble-based methodology and iteratively combines classifiers in order to assign weights to features characterizing their importance in cl
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c2ec321b749d5c404b38935a62f66dbe
https://doi.org/10.13187/ejtd.2013.1.70
https://doi.org/10.13187/ejtd.2013.1.70
Autor:
Yulia A. Zhuk, Lev V. Utkin
Publikováno v:
Knowledge and Information Systems. 41:53-76
An extension of Campbell and Bennett's novelty detection or one-class classification model incorporating prior knowledge is studied in the paper. The proposed extension relaxes the strong assumption of the empirical probability distribution over elem
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2ff252aaafd25ca195a1731c1ce17e2c
https://doi.org/10.1007/s10115-013-0661-7
https://doi.org/10.1007/s10115-013-0661-7
Publikováno v:
Neural networks : the official journal of the International Neural Network Society. 80
Classification algorithms based on different forms of support vector machines (SVMs) for dealing with interval-valued training data are proposed in the paper. L 2 -norm and L ∞ -norm SVMs are used for constructing the algorithms. The main idea allo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::93d74dc0041db9778a8c78d5aecd9b35
https://pubmed.ncbi.nlm.nih.gov/27179616
https://pubmed.ncbi.nlm.nih.gov/27179616
Autor:
Yulia A. Zhuk, Lev V. Utkin
Publikováno v:
International Journal on Artificial Intelligence Tools. 26:1750014
A new robust SVM-based algorithm of the binary classification is proposed. It is based on the so-called uncertainty trick when training data with the interval uncertainty are transformed to training data with the weight or probabilistic uncertainty.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::577a635bdc83cf12ce9b853e45a5e80a
https://doi.org/10.1142/s0218213017500142
https://doi.org/10.1142/s0218213017500142
Publikováno v:
Machine Learning and Data Mining in Pattern Recognition ISBN: 9783319089782
MLDM
MLDM
A robust model for solving the one-class classification problem by interval-valued training data is proposed in the paper. It is based on using Dempster-Shafer theory for getting the lower and upper risk measures. The minimax or pessimistic strategy
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::966d4b5ef588e882fa0373c1551cf0ee
https://doi.org/10.1007/978-3-319-08979-9_9
https://doi.org/10.1007/978-3-319-08979-9_9
Autor:
Lev V. Utkin, Yulia A. Zhuk
Publikováno v:
Advances in Artificial Intelligence.
A method for solving a classification problem when there is only partial information about some features is proposed. This partial information comprises the mean values of features for every class and the bounds of the features. In order to maximally
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::034f362ab78ebd1cb51dca28592ddb96