dtwclust: Time Series Clustering Along with Optimizations for the Dynamic Time Warping Distance (original) (raw)

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.

Version: 6.0.0
Depends: R (≥ 3.3.0), methods, proxy (≥ 0.4-16), dtw
Imports: parallel, stats, utils, clue, cluster, dplyr, flexclust, foreach, ggplot2, ggrepel, rlang, Matrix (≥ 1.5-0), RSpectra, Rcpp, RcppParallel (≥ 4.4.0), reshape2, shiny, shinyjs
LinkingTo: Rcpp, RcppArmadillo, RcppParallel, RcppThread
Suggests: doParallel, iterators, knitr, rmarkdown, testthat
Published: 2024-07-23
DOI: 10.32614/CRAN.package.dtwclust
Author: Alexis Sarda-Espinosa
Maintainer: Alexis Sarda <alexis.sarda at gmail.com>
BugReports: https://github.com/asardaes/dtwclust/issues
License: GPL-3
Copyright: see file
URL: https://github.com/asardaes/dtwclust
NeedsCompilation: yes
SystemRequirements: GNU make
Citation: dtwclust citation info
Materials: NEWS
In views: TimeSeries
CRAN checks: dtwclust results

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