Classifying and analyzing small‐angle scattering data using weighted k nearest neighbors machine learning techniques

A consistent challenge for both new and expert practitioners of small‐angle scattering (SAS) lies in determining how to analyze the data, given the limited information content of said data and the large number of models that can be employed. Machine learning (ML) methods are powerful tools for class...

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Veröffentlicht in:	Journal of applied crystallography 2020-04, Vol.53 (2), p.326-334
Hauptverfasser:	Archibald, Richard K., Doucet, Mathieu, Johnston, Travis, Young, Steven R., Yang, Erika, Heller, William T.
Format:	Artikel
Sprache:	eng
Schlagworte:	Classification Data analysis Gaussian process Learning algorithms Machine learning MATHEMATICS AND COMPUTING modeling SasView Scattering small-angle scattering data
Online-Zugang:	Volltext
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