Clustering of functional data in a low-dimensional subspace

DOI10.1007/s11634-012-0113-3zbMath1254.62077OpenAlexW2019084556MaRDI QIDQ695680

Michio Yamamoto

Publication date: 14 December 2012

Published in: Advances in Data Analysis and Classification. ADAC (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11634-012-0113-3

zbMATH Keywords

smoothingdimension reduction

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30)

Related Items (8)

A survey of functional principal component analysis ⋮ Functional factorial \(K\)-means analysis ⋮ Dimension-reduced clustering of functional data via subspace separation ⋮ Functional data clustering via hypothesis testing \(k\)-means ⋮ Functional data clustering: a survey ⋮ Efficient regularized spectral data embedding ⋮ Independent component analysis for multivariate functional data ⋮ Clustering multivariate functional data in group-specific functional subspaces

Uses Software

• R
• fda (R)
• funHDDC

Cites Work

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• Factorial and reduced \(K\)-means reconsidered
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• Least squares quantization in PCM
• A Functional Data Analysis of the Pinch Force of Human Fingers
• Factorial \(k\)-means analysis for two-way data.
• A practical guide to splines.

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