Benchmark and application of unsupervised classification approaches for univariate data

In the field of nanoscience, clustering methods have gained momentum for the analysis of experimental datasets with the aim of uncovering new physical properties. Here, the authors describe an unsupervised machine learning methodology that selects the optimal combination of feature space, clustering...

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Auteurs principaux: Maria El Abbassi, Jan Overbeck, Oliver Braun, Michel Calame, Herre S. J. van der Zant, Mickael L. Perrin
Format: article
Langue:EN
Publié: Nature Portfolio 2021
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Accès en ligne:https://doaj.org/article/142f18d37da342038eb2d52cf28bd1d9
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