Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 14, issue 3
Articles | Volume 14, issue 3
https://doi.org/10.5194/gmd-14-1553-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-14-1553-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 14, issue 3
Model description paper
 | 
17 Mar 2021
Model description paper |  | 17 Mar 2021

MLAir (v1.0) – a tool to enable fast and flexible machine learning on air data time series

Lukas Hubert Leufen, Felix Kleinert, and Martin G. Schultz

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Latest update: 19 Apr 2024
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Short summary
MLAir provides a coherent end-to-end structure for a typical time series analysis workflow using machine learning (ML). MLAir is adaptable to a wide range of ML use cases, focusing in particular on deep learning. The user has a free hand with the ML model itself and can select from different methods during preprocessing, training, and postprocessing. MLAir offers tools to track the experiment conduction, documents necessary ML parameters, and creates a variety of publication-ready plots.
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