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Estimating the intrinsic dimension of datasets by a minimal neighborhood information

Analyzing large volumes of high-dimensional data is an issue of fundamental importance in data science, molecular simulations and beyond. Several approaches work on the assumption that the important content of a dataset belongs to a manifold whose Intrinsic Dimension (ID) is much lower than the crud...

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Detalles Bibliográficos
Autores principales: Facco, Elena, d’Errico, Maria, Rodriguez, Alex, Laio, Alessandro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5610237/
https://www.ncbi.nlm.nih.gov/pubmed/28939866
http://dx.doi.org/10.1038/s41598-017-11873-y