Become an expert in R — Interactive courses, Cheat Sheets, certificates and more!
Get Started for Free

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. Implementations of DTW barycenter averaging, a distance based on global alignment kernels, and the soft-DTW distance and centroid routines are also provided. All included distance functions have custom loops optimized for the calculation of cross-distance matrices, including parallelization support. Several cluster validity indices are included.

Functions (43)

dtwclust

Time Series Clustering Along with Optimizations for the Dynamic Time Warping Distance

v5.5.10
GPL-3
Authors
Alexis Sarda-Espinosa
Initial release
2022-04-15

We don't support your browser anymore

Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.