Robust and Scalable Learning of Complex Intrinsic Dataset Geometry via ElPiGraph

Multidimensional datapoint clouds representing large datasets are frequently characterized by non-trivial low-dimensional geometry and topology which can be recovered by unsupervised machine learning approaches, in particular, by principal graphs. Principal graphs approximate the multivariate data b...

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Detalles Bibliográficos
Autores principales: Albergante, Luca, Mirkes, Evgeny, Bac, Jonathan, Chen, Huidong, Martin, Alexis, Faure, Louis, Barillot, Emmanuel, Pinello, Luca, Gorban, Alexander, Zinovyev, Andrei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7516753/
https://www.ncbi.nlm.nih.gov/pubmed/33286070
http://dx.doi.org/10.3390/e22030296

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7516753/
https://www.ncbi.nlm.nih.gov/pubmed/33286070
http://dx.doi.org/10.3390/e22030296

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