Have a personal or library account? Click to login
Improving the Performance of the Feature Drift Detector by Lasso Observation of Sample Feature Fluctuations Cover

Improving the Performance of the Feature Drift Detector by Lasso Observation of Sample Feature Fluctuations

International Journal of Applied Mathematics and Computer Science
Volume 35 (2025): Issue 4 (December 2025)
By: Piotr Porwik,  Tomasz Orczyk and  Nathalie Japkowicz  
Open Access
|Dec 2025

Authors

Piotr Porwik

piotr.porwik@us.edu.pl

Institute of Computer Science, University of Silesia ul, Sosnowiec, Poland

Tomasz Orczyk

tomasz.orczyk@us.edu.pl

Institute of Computer Science, University of Silesia ul, Sosnowiec, Poland

Nathalie Japkowicz

japkowic@american.edu

Computer Science Department, American University, Washington, DC, USA
DOI: https://doi.org/10.61822/amcs-2025-0049 | Journal eISSN: 2083-8492 | Journal ISSN: 1641-876X
Journal RSS Feed
Language: English
Page range: 687 - 702
Submitted on: Apr 18, 2025
Accepted on: Sep 17, 2025
Published on: Dec 15, 2025
Published by: University of Zielona Góra
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year
Keywords:
feature drift,
data stream,
drift detection,
feature ranking,
classification
Related subjects:
Mathematics,
Applied mathematics

© 2025 Piotr Porwik, Tomasz Orczyk, Nathalie Japkowicz, published by University of Zielona Góra
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Previous articleVolume 35 (2025): Issue 4 (December 2025)Next article