Robust and Scalable Learning of Complex Intrinsic Dataset Geometry via ElPiGraph

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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Bibliographic Details
Main Authors: Luca Albergante, Evgeny Mirkes, Jonathan Bac, Huidong Chen, Alexis Martin, Louis Faure, Emmanuel Barillot, Luca Pinello, Alexander Gorban, Andrei Zinovyev
Format: Article
Language:English
Published: MDPI AG 2020-03-01
Series:Entropy
Subjects:
data approximation
principal graphs
principal trees
topological grammars
software
Online Access:https://www.mdpi.com/1099-4300/22/3/296

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