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clusTransition: An R package for monitoring transition in cluster solutions of temporal datasets
Clustering analysis’ primary purpose is to divide a dataset into a finite number of segments based on the similarities between items. In recent years, a significant amount of study has focused on the spatio-temporal aspects of clustering. However, clusters are no longer regarded as static objects si...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9754593/ https://www.ncbi.nlm.nih.gov/pubmed/36520935 http://dx.doi.org/10.1371/journal.pone.0278146 |
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author | Atif, Muhammad Leisch, Friedrich |
author_facet | Atif, Muhammad Leisch, Friedrich |
author_sort | Atif, Muhammad |
collection | PubMed |
description | Clustering analysis’ primary purpose is to divide a dataset into a finite number of segments based on the similarities between items. In recent years, a significant amount of study has focused on the spatio-temporal aspects of clustering. However, clusters are no longer regarded as static objects since changes influence them in the underlying population. This paper describes an R package implementing the MONIC framework for tracing the evolution of clusters extracted from temporal datasets. The name of the package is clusTransition, which stands for Cluster Transition. The algorithm is based on re-clustering cumulative datasets that evolve at successive time-points and monitoring the transitions experienced by the clusters in these clustering solutions. This paper’s contribution is to demonstrate how the package clusTransition is developed in the R programming language, and its workflow is discussed using hypothetical and real-life datasets. |
format | Online Article Text |
id | pubmed-9754593 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-97545932022-12-16 clusTransition: An R package for monitoring transition in cluster solutions of temporal datasets Atif, Muhammad Leisch, Friedrich PLoS One Research Article Clustering analysis’ primary purpose is to divide a dataset into a finite number of segments based on the similarities between items. In recent years, a significant amount of study has focused on the spatio-temporal aspects of clustering. However, clusters are no longer regarded as static objects since changes influence them in the underlying population. This paper describes an R package implementing the MONIC framework for tracing the evolution of clusters extracted from temporal datasets. The name of the package is clusTransition, which stands for Cluster Transition. The algorithm is based on re-clustering cumulative datasets that evolve at successive time-points and monitoring the transitions experienced by the clusters in these clustering solutions. This paper’s contribution is to demonstrate how the package clusTransition is developed in the R programming language, and its workflow is discussed using hypothetical and real-life datasets. Public Library of Science 2022-12-15 /pmc/articles/PMC9754593/ /pubmed/36520935 http://dx.doi.org/10.1371/journal.pone.0278146 Text en © 2022 Atif, Leisch https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Atif, Muhammad Leisch, Friedrich clusTransition: An R package for monitoring transition in cluster solutions of temporal datasets |
title | clusTransition: An R package for monitoring transition in cluster solutions of temporal datasets |
title_full | clusTransition: An R package for monitoring transition in cluster solutions of temporal datasets |
title_fullStr | clusTransition: An R package for monitoring transition in cluster solutions of temporal datasets |
title_full_unstemmed | clusTransition: An R package for monitoring transition in cluster solutions of temporal datasets |
title_short | clusTransition: An R package for monitoring transition in cluster solutions of temporal datasets |
title_sort | clustransition: an r package for monitoring transition in cluster solutions of temporal datasets |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9754593/ https://www.ncbi.nlm.nih.gov/pubmed/36520935 http://dx.doi.org/10.1371/journal.pone.0278146 |
work_keys_str_mv | AT atifmuhammad clustransitionanrpackageformonitoringtransitioninclustersolutionsoftemporaldatasets AT leischfriedrich clustransitionanrpackageformonitoringtransitioninclustersolutionsoftemporaldatasets |