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dtwclust (version 6.0.0)

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

Description

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.

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Install

install.packages('dtwclust')

Monthly Downloads

3,683

Version

6.0.0

License

GPL-3

Issues

Pull Requests

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Repository

https://github.com/asardaes/dtwclust

Maintainer

Alexis Sarda

Last Published

July 23rd, 2024

Functions in dtwclust (6.0.0)

Cluster validity indices

SparseDistmat-class

Sparse distance matrix

compute_envelope

Time series warping envelopes

TSClusters-class

Class definition for TSClusters and derived classes

DTW distance with L2 norm

Cluster comparison based on CVIs

compare_clusterings

Compare different clustering configurations

Basic DTW distance

compare_clusterings_configs

Create clustering configurations.

DTW distance matrix guided by Lemire's improved lower bound

Keogh's DTW lower bound

Centroid for partition around medoids

SparseDistmat-generics

Generics for SparseDistmat

interactive_clustering

A shiny app for interactive clustering

Lemire's improved DTW lower bound

TADPole clustering

shape_extraction

Shape average of several time series

explore__tidy_series

This helper will create the data frame used to plot in the Explore tab panel

Distmat-generics

Generics for Distmat

dtwclust-package

Time series clustering along with optimizations for the Dynamic Time Warping distance

This helper will produce the plot in the Explore tab panel.

A shiny app for semi-supervised DTW-based clustering

tsclust-controls

Control parameters for clusterings with tsclust()

Time series clustering

dtwclustTimings

Results of timing experiments

Soft-DTW distance

Centroid calculation based on soft-DTW

DistmatLowerTriangular-class

Distance matrix's lower triangular

Subset of character trajectories data set

Coerce matrices or data frames to a list of time series

This helper will parse comma-separated key-value pairs

tsclustFamily-class

Class definition for tsclustFamily

Helper function for preprocessing/distance/centroid configurations

Wrapper for simple linear reinterpolation

repeat_clustering

Repeat a clustering configuration

Wrapper for z-normalization

tsclusters-methods

Methods for TSClusters

Cross-correlation with coefficient normalization

Shape-based distance

Fast global alignment kernels

DTW Barycenter Averaging

PairTracker-class

Helper for semi-supervised DTW clustering

DistmatLowerTriangular-generics

Generics for DistmatLowerTriangular

Distance matrix