EigenWorms_2: EigenWorms_2

In mlmts: Machine Learning Algorithms for Multivariate Time Series

EigenWorms_2

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_2)

Format

A list with two elements, which are:

data

A list with 129 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 last 129 elements of the whole dataset are stored here. All these elements pertain to the test 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 \insertCitebagnall2018uea;textualmlmts. To access this dataset, run "install.packages("ueadata6", repos="https://anloor7.github.io/drat")" and use the syntax "ueadata6::EigenWorms_2".

References

\insertRef

bagnall2018ueamlmts

\insertRef

ruiz2021greatmlmts

\insertRef

bagnallwebmlmts

mlmts documentation built on Sept. 11, 2024, 6:41 p.m.