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Comparative analysis of the performance of selected machine learning algorithms depending on the size of the training sample Cover

Comparative analysis of the performance of selected machine learning algorithms depending on the size of the training sample

Reports on Geodesy and Geoinformatics
Volume 118 (2024): Issue 1 (December 2024)
By: Przemysław Kupidura,  Agnieszka Kępa and  Piotr Krawczyk  
Open Access
|Sep 2024

Authors

Przemysław Kupidura

przemyslaw.kupidura@pw.edu.pl

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

Agnieszka Kępa

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

Piotr Krawczyk

Orbitile Ltd, Warsaw, Poland
DOI: https://doi.org/10.2478/rgg-2024-0015 | Journal eISSN: 2391-8152 | Journal ISSN: 0867-3179
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Language: English
Submitted on: Mar 13, 2024
Accepted on: Jul 29, 2024
Published on: Sep 26, 2024
Published by: Warsaw University of Technology
In partnership with: Paradigm Publishing Services
Publication frequency: 2 issues per year
Keywords:
efficiency,
classification,
machine learning,
remote sensing,
satellite imagery,
training sample size
Related subjects:
Computer sciences,
Computer sciences, other,
Geosciences,
Geodesy,
Cartography and photogrammetry,
Geosciences, other

© 2024 Przemysław Kupidura, Agnieszka Kępa, Piotr Krawczyk, published by Warsaw University of Technology
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

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