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Impact of Feature Choice on Machine Learning Classification of Fractional Anomalous Diffusion
The growing interest in machine learning methods has raised the need for a careful study of their application to the experimental single-particle tracking data. In this paper, we present the differences in the classification of the fractional anomalous diffusion trajectories that arise from the sele...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2020
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7767296/ https://www.ncbi.nlm.nih.gov/pubmed/33352694 http://dx.doi.org/10.3390/e22121436 |