Digital Library of Zielona Góra contains 63 052 digital objects
Object
Title: Regression function and noise variance tracking methods for data streams with concept drift
Contributor:
Korbicz, Józef (1951- ) - red. ; Uciński, Dariusz - red.
Group publication title:
Abstract:
Two types of heuristic estimators based on Parzen kernels are presented. They are able to estimate the regression function in an incremental manner. The estimators apply two techniques commonly used in concept-drifting data streams, i.e., the forgetting factor and the sliding window. The methods are applicable for models in which both the function and the noise variance change over time. Although nonparametric methods based on Parzen kernels were previously successfully applied in the literature to online regression function estimation, the problem of estimating the variance of noise was generally neglected. ; It is sometimes of profound interest to know the variance of the signal considered, e.g., in economics, but it can also be used for determining confidence intervals in the estimation of the regression function, as well as while evaluating the goodness of fit and in controlling the amount of smoothing. The present paper addresses this issue. Specifically, variance estimators are proposed which are able to deal with concept drifting data by applying a sliding window and a forgetting factor, respectively. A number of conducted numerical experiments proved that the proposed methods perform satisfactorily well in estimating both the regression function and the variance of the noise.
Publisher:
Zielona Góra: Uniwersytet Zielonogórski
Resource Identifier:
DOI:
Pages:
Source:
AMCS, volume 28, number 3 (2018) ; click here to follow the link
Language:
License CC BY 4.0:
Rights:
Biblioteka Uniwersytetu Zielonogórskiego
Object collections:
- Digital Library of Zielona Góra > Repository > Faculties > Faculty of Computer, Electrical and Control Engineering
- Digital Library of Zielona Góra > Repository > Types of work > Articles
- Digital Library of Zielona Góra > Repository > Scientific journals and UZ publishing series > International Journal of Applied Mathematics and Computer Science (AMCS) > International Journal of Applied Mathematics and Computer Science (AMCS) (2018)
Last modified:
Jul 14, 2025
In our library since:
Jul 9, 2025
Number of object content hits:
13
All available object's versions:
https://zbc.uz.zgora.pl/publication/100869
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 28, number 1 (2018)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 28, number 2 (2018)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 28, number 3 (2018)
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International Journal of Applied Mathematics and Computer Science (AMCS), volume 28, number 4 (2018)
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| Edition name | Date |
|---|---|
| Regression function and noise variance tracking methods for data streams with concept drift | Jul 14, 2025 |
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