Benchmarking different clustering algorithms on functional data

DOI10.1007/s11634-016-0261-yzbMath1414.62289OpenAlexW2470089128WikidataQ57066209 ScholiaQ57066209MaRDI QIDQ2418320

Friedrich Leisch, Christina Yassouridis

Publication date: 3 June 2019

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

Full work available at URL: https://doi.org/10.1007/s11634-016-0261-y

zbMATH Keywords

benchmarkingfunctional clusteringhyperparameters

Mathematics Subject Classification ID

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

Related Items

Robust clustering of functional directional data ⋮ Cluster analysis with cellwise trimming and applications for the robust clustering of curves ⋮ A fast epigraph and hypograph-based approach for clustering functional data

Uses Software

• R
• MASS (R)
• wavethresh
• curvclust

Cites Work

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• Distance-based clustering of sparsely observed stochastic processes, with applications to online auctions
• Statistical Analysis of Financial Data in S-Plus
• Time-synchronized clustering of gene expression trajectories
• A Comparison of Hierarchical Methods for Clustering Functional Data
• Clustering for Sparsely Sampled Functional Data
• Wavelet‐Based Clustering for Mixed‐Effects Functional Models in High Dimension
• Functional Clustering and Identifying Substructures of Longitudinal Data
• Mercer’s Theorem, Feature Maps, and Smoothing

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