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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Autors principals:	Luca Albergante, Evgeny Mirkes, Jonathan Bac, Huidong Chen, Alexis Martin, Louis Faure, Emmanuel Barillot, Luca Pinello, Alexander Gorban, Andrei Zinovyev
Format:	Artigo
Idioma:	Inglês
Publicat:	MDPI AG 2020-03-01
Col·lecció:	Entropy
Matèries:	data approximation principal graphs principal trees topological grammars software
Accés en línia:	https://www.mdpi.com/1099-4300/22/3/296
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