Data

Data set for article: Effect of data preprocessing and machine learning hyperparameters on mass spectrometry imaging models

La Trobe University
Wil Gardner (Aggregated by)
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ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.26181/22671022.v1&rft.title=Data set for article: Effect of data preprocessing and machine learning hyperparameters on mass spectrometry imaging models&rft.identifier=10.26181/22671022.v1&rft.publisher=La Trobe University&rft.description=This data set is uploaded as supporting information for the publication entitled:Effect of data preprocessing and machine learning hyperparameters on mass spectrometry imaging modelsFiles are as follows:polymer_microarray_data.mat - MATLAB workspace file containing peak-picked ToF-SIMS data (hyperspectral array) for the polymer microarray sample.nylon_data.mat - MATLAB workspace file containing m/z binned ToF-SIMS data (hyperspectral array) for the semi-synthetic nylon data set, generated from 7 nylon samples.Additional details about the datasets can be found in the published article.If you use this data set in your work, please cite our work as follows:Cite as: Gardner et al.. J. Vac. Sci. Technol. A 41, 000000 (2023); doi: 10.1116/6.0002788&rft.creator=Wil Gardner&rft.date=2023&rft_rights= https://creativecommons.org/licenses/by-nc-sa/4.0/&rft_rights=© The authors 2023. This dataset is open access distributed under the terms and conditions of the Creative Commons Attribution-ShareAlike license:\nhttps://creativecommons.org/licenses/by-nc-sa/4.0/&rft_subject=Other physical sciences not elsewhere classified&rft_subject=Structural properties of condensed matter&rft_subject=Surface properties of condensed matter&rft_subject=self-organising map&rft_subject=machine learning&rft_subject=tof-sims&rft_subject=Applied Physics&rft_subject=Surfaces and Structural Properties of Condensed Matter&rft.type=dataset&rft.language=English Access the data
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https://creativecommons.org/licenses/by-nc-sa/4.0/

© The authors 2023. This dataset is open access distributed under the terms and conditions of the Creative Commons Attribution-ShareAlike license:\nhttps://creativecommons.org/licenses/by-nc-sa/4.0/

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This data set is uploaded as supporting information for the publication entitled:

Effect of data preprocessing and machine learning hyperparameters on mass spectrometry imaging models

Files are as follows:

polymer_microarray_data.mat - MATLAB workspace file containing peak-picked ToF-SIMS data (hyperspectral array) for the polymer microarray sample.

nylon_data.mat - MATLAB workspace file containing m/z binned ToF-SIMS data (hyperspectral array) for the semi-synthetic nylon data set, generated from 7 nylon samples.

Additional details about the datasets can be found in the published article.

If you use this data set in your work, please cite our work as follows:

Cite as: Gardner et al.. J. Vac. Sci. Technol. A 41, 000000 (2023); doi: 10.1116/6.0002788

Issued: 22 09 2023

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Applied Physics | Other physical sciences not elsewhere classified | Structural properties of condensed matter | Surface properties of condensed matter | Surfaces and Structural Properties of Condensed Matter | machine learning | self-organising map | tof-sims |

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