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Clustering functional data using forward search based on functional spatial ranks with medical applications

Cluster analysis of functional data is finding increasing application in the field of medical research and statistics. Here we introduce a functional version of the forward search methodology for the purpose of functional data clustering. The proposed forward search algorithm is based on the functio...

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Detalles Bibliográficos
Autores principales: Baragilly, Mohammed, Gabr, Hend, Willis, Brian H
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8721557/
https://www.ncbi.nlm.nih.gov/pubmed/34756132
http://dx.doi.org/10.1177/09622802211002865
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author Baragilly, Mohammed
Gabr, Hend
Willis, Brian H
author_facet Baragilly, Mohammed
Gabr, Hend
Willis, Brian H
author_sort Baragilly, Mohammed
collection PubMed
description Cluster analysis of functional data is finding increasing application in the field of medical research and statistics. Here we introduce a functional version of the forward search methodology for the purpose of functional data clustering. The proposed forward search algorithm is based on the functional spatial ranks and is a data-driven non-parametric method. It does not require any preprocessing functional data steps, nor does it require any dimension reduction before clustering. The Forward Search Based on Functional Spatial Rank (FSFSR) algorithm identifies the number of clusters in the curves and provides the basis for the accurate assignment of each curve to its cluster. We apply it to three simulated datasets and two real medical datasets, and compare it with six other standard methods. Based on both simulated and real data, the FSFSR algorithm identifies the correct number of clusters. Furthermore, when compared with six standard methods used for clustering and classification, it records the lowest misclassification rate. We conclude that the FSFSR algorithm has the potential to cluster and classify functional data.
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spelling pubmed-87215572022-01-04 Clustering functional data using forward search based on functional spatial ranks with medical applications Baragilly, Mohammed Gabr, Hend Willis, Brian H Stat Methods Med Res Articles Cluster analysis of functional data is finding increasing application in the field of medical research and statistics. Here we introduce a functional version of the forward search methodology for the purpose of functional data clustering. The proposed forward search algorithm is based on the functional spatial ranks and is a data-driven non-parametric method. It does not require any preprocessing functional data steps, nor does it require any dimension reduction before clustering. The Forward Search Based on Functional Spatial Rank (FSFSR) algorithm identifies the number of clusters in the curves and provides the basis for the accurate assignment of each curve to its cluster. We apply it to three simulated datasets and two real medical datasets, and compare it with six other standard methods. Based on both simulated and real data, the FSFSR algorithm identifies the correct number of clusters. Furthermore, when compared with six standard methods used for clustering and classification, it records the lowest misclassification rate. We conclude that the FSFSR algorithm has the potential to cluster and classify functional data. SAGE Publications 2021-11-10 2022-01 /pmc/articles/PMC8721557/ /pubmed/34756132 http://dx.doi.org/10.1177/09622802211002865 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle Articles
Baragilly, Mohammed
Gabr, Hend
Willis, Brian H
Clustering functional data using forward search based on functional spatial ranks with medical applications
title Clustering functional data using forward search based on functional spatial ranks with medical applications
title_full Clustering functional data using forward search based on functional spatial ranks with medical applications
title_fullStr Clustering functional data using forward search based on functional spatial ranks with medical applications
title_full_unstemmed Clustering functional data using forward search based on functional spatial ranks with medical applications
title_short Clustering functional data using forward search based on functional spatial ranks with medical applications
title_sort clustering functional data using forward search based on functional spatial ranks with medical applications
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8721557/
https://www.ncbi.nlm.nih.gov/pubmed/34756132
http://dx.doi.org/10.1177/09622802211002865
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