Model-Free Cluster Analysis of Physical Property Data using Information Maximizing Self-Argument Training

We present semi-supervised information maximizing self-argument training (IMSAT), a neural network-based classification method that works without the preparation of labeled data. Semi-supervised IMSAT can amplify specific differences and avoid undesirable misclassification in accordance with the pur...

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Detalles Bibliográficos
Autores principales: Sawada, Ryohto, Iwasaki, Yuma, Ishida, Masahiko
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7221089/
https://www.ncbi.nlm.nih.gov/pubmed/32404915
http://dx.doi.org/10.1038/s41598-020-64281-0

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7221089/
https://www.ncbi.nlm.nih.gov/pubmed/32404915
http://dx.doi.org/10.1038/s41598-020-64281-0

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