R package dtwclust: Time Series Clustering Along with Optimizations for the Dynamic Time Warping Distance. Time series clustering along with optimized techniques related to the Dynamic Time Warping distance and its corresponding lower bounds. Implementations of partitional, hierarchical, fuzzy, k-Shape and TADPole clustering are available. Functionality can be easily extended with custom distance measures and centroid definitions.
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References in zbMATH (referenced in 3 articles )
Showing results 1 to 3 of 3.
- Loliencar, Prachi; Heo, Giseon: Phenotyping OSA: a time series analysis using fuzzy clustering and persistent homology (2022)
- Alonso, Andrés M.; D’Urso, Pierpaolo; Gamboa, Carolina; Guerrero, Vanesa: Cophenetic-based fuzzy clustering of time series by linear dependency (2021)
- Maximilian Leodolter, Claudia Plant, Norbert Brändle: IncDTW: An R Package for Incremental Calculation of Dynamic Time Warping (2021) not zbMATH