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dtwclust (version 2.1.1)

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 k-Shape, TADPole and fuzzy clustering are available. The functionality can be easily extended with custom distance measures and centroid definitions.

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Install

install.packages('dtwclust')

Monthly Downloads

3,683

Version

2.1.1

License

GPL-3

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Repository

https://github.com/asardaes/dtwclust

Maintainer

Alexis Sarda

Last Published

March 20th, 2016

Functions in dtwclust (2.1.1)

Time series clustering

dtwclustFamily-class

Class definition for dtwclustFamily

Cross-correlation with coefficient normalization

Compare partitions

TADPole clustering

Lemire's improved DTW lower bound

Subset of character trajectories data set

DTW Barycenter Averaging

dtwclustControl-class

Class definition for dtwclustControl

Cluster Similarity Matrix

DTW calculation guided by Lemire's lower bounds

Keogh's DTW lower bound

dtwclust-methods

Methods for dtwclust

Shape-based distance

shape_extraction

Shape average of several time series

Wrapper for simple linear reinterpolation

dtwclust-package

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

Class definition for dtwclust

Wrapper for z-normalization