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Evaluating machine learning algorithms: The role of sample size and quality Cover

Evaluating machine learning algorithms: The role of sample size and quality

Reports on Geodesy and Geoinformatics
Volume 122 (2026): Issue 1 (December 2026)
By:  and    
Open Access
|Jul 2026
Authors

Authors

Przemysław Kupidura

przemyslaw.kupidura@pw.edu.pl

Faculty of Geodesy and Cartography, Warsaw University of Technology, Warsaw, Poland

Michał Szkibiel

Faculty of Geodesy and Cartography, Warsaw University of Technology, Warsaw, Poland
DOI: https://doi.org/10.2478/rgg-2026-0007 | Journal eISSN: 2391-8152 | Journal ISSN: 0867-3179
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Language: English
Page range: 1 - 13
Published on: Jul 28, 2026
Published by: Warsaw University of Technology
In partnership with: Paradigm Publishing Services
Publication frequency: 2 issues per year
Keywords:
overfitting,
land cover classification,
remote sensing,
supervised machine learning,
training sample size,
model robustness
Related subjects:
Computer sciences,
Computer sciences, other,
Geosciences,
Geodesy,
Cartography and photogrammetry,
Geosciences, other

© 2026 Przemysław Kupidura, Michał Szkibiel, published by Warsaw University of Technology
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Volume 122 (2026): Issue 1 (December 2026)