clusEvol: An R package for Cluster Evolution Analytics
The paper proposes a new R package, named clusEvol , that introduces Cluster Evolution Analytics (CEA), a framework for advanced Exploratory Data Analysis and Unsupervised Learning. CEA studies the evolution of an object and its neighbors, identified via clustering algorithms, over time. It combines leave-one-out and plug-in principles, enabling “what if” scenarios by integrating current data into past datasets to explore temporal changes. The framework is demonstrated with a real dataset employing various clustering algorithms.
Authors
- Bolívar Morales-Oñate (ORCID: https://orcid.org/0000-0003-4980-8759)
- Víctor Morales‐Oñate (ORCID: https://orcid.org/0000-0003-1922-6571)
Institutions
- Universidad de Las Américas (EC)
- Escuela Superior Politécnica del Chimborazo (EC)
Publication Details
- Journal
- SoftwareX
- Published
- 2024-10-17
- DOI
- https://doi.org/10.1016/j.softx.2024.101921
- Primary Topic
- Advanced Clustering Algorithms Research
- Type
- article
- Field-Weighted Citation Impact
- 0.35