Clustering multivariate functional data using unsupervised binary trees

•An effective model-based clustering algorithm for multivariate functional data.•The algorithm is recursive and based on a set of binary trees.•The number of clusters is determined in a data-driven way.•New data are easily classified. A model-based clustering algorithm is proposed for a general clas...

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Veröffentlicht in:	Computational statistics & data analysis Jg. 168; S. 107376
Hauptverfasser:	Golovkine, Steven, Klutchnikoff, Nicolas, Patilea, Valentin
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 01.04.2022 Elsevier
Schlagworte:	algorithms data analysis data collection Gaussian mixtures Machine Learning Model-based clustering Multivariate functional principal components Statistics Gaussian mixtures Model-based clustering Multivariate functional principal components Multivariate Functional Principal Components
ISSN:	0167-9473, 1872-7352
Online-Zugang:	Volltext
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