EigenWorms_1 {mlmts}

EigenWorms_1

Description

Multivariate time series (MTS) indicating the movement of the worm Caenorhabditis elegans. The motion of worms in an agar plate is recorded as a combination of six base shapes.

Usage

data(EigenWorms_1)

Format

A list with two elements, which are:

data

A list with 130 MTS.

classes

A numeric vector indicating the corresponding classes associated with the elements in data.

Details

Each element in data is a matrix formed by 17984 rows (time points) indicating velocity trajectory and 3 columns (variables) indicating spatial dimension. The first 1422 elements correspond to the training set, whereas the last 1436 elements correspond to the test set. The first 130 elements of the whole dataset are stored here. All these elements but the last two pertain to the training set. The numeric vector classes is formed by integers from 1 to 20, indicating that there are 20 different classes in the database. Each class is associated with a different alphabetical character. For more information, see Bagnall et al. (2018). To access this dataset, run "install.packages("ueadata5", repos="https://anloor7.github.io/drat")" and use the syntax "ueadata5::EigenWorms_1".

References

Bagnall A, Dau HA, Lines J, Flynn M, Large J, Bostrom A, Southam P, Keogh E (2018). “The UEA multivariate time series classification archive, 2018.” arXiv preprint arXiv:1811.00075.

Ruiz AP, Flynn M, Large J, Middlehurst M, Bagnall A (2021). “The great multivariate time series classification bake off: a review and experimental evaluation of recent algorithmic advances.” Data Mining and Knowledge Discovery, 35(2), 401–449.

Bagnall A, Lines J, Vickers W, Keogh E (2022). “The UEA & UCR Time Series Classification Repository.” www.timeseriesclassification.com.