Clustering and Topological Data Analysis: Comparison and Application

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dc.contributor.authorCombs, Kara
dc.contributor.authorBihl, Trevor
dc.date.accessioned2022-12-27T18:55:26Z
dc.date.available2022-12-27T18:55:26Z
dc.date.issued2023-01-03
dc.description.abstractClustering is common technique used to demonstrate relationships between data and information. Of recent interest is topological data analysis (TDA), which can represent and cluster data through persistent homology. The TDA algorithms used include the Topological Mode Analysis Tool (ToMATo) algorithm, Garin and Tauzin’s TDA Pipeline, and the Mapper algorithm. First, TDA is compared to ten other clustering algorithms on artificial 2D data where it ranked third overall. TDA had the second-highest performance in terms of average accuracy (97.9%); however, its computation-time performance ranked in the middle of the algorithms. TDA ranked fourth on the qualitative “visual trustworthiness” metric. On real-world data, TDA showed promising classification results (accuracy between 80-95%). Overall, this paper shows TDA is a competitive algorithm performance-wise, though computationally expensive. When TDA is used for visualization, the Mapper algorithm allows for unique alternative views especially effective for visualizing highly dimensional data.
dc.format.extent10
dc.identifier.doi10.24251/HICSS.2023.102
dc.identifier.isbn978-0-9981331-6-4
dc.identifier.other46941403-8a51-4d6a-8990-45ba424d170f
dc.identifier.urihttps://hdl.handle.net/10125/102731
dc.language.isoeng
dc.relation.ispartofProceedings of the 56th Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectBig Data and Analytics: Pathways to Maturity
dc.subjectalgorithm trust
dc.subjectbig data
dc.subjectclustering
dc.subjectheuristic analysis
dc.subjecttopological data analysis
dc.titleClustering and Topological Data Analysis: Comparison and Application
dc.type.dcmitext
prism.startingpage815

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