mlmts: Machine Learning Algorithms for Multivariate Time Series

An implementation of several machine learning algorithms for multivariate time series. The package includes functions allowing the execution of clustering, classification or outlier detection methods, among others. It also incorporates a collection of multivariate time series datasets which can be used to analyse the performance of new proposed algorithms. Some of these datasets are stored in GitHub data packages 'ueadata1' to 'ueadata8'. To access these data packages, run 'install.packages(c('ueadata1', 'ueadata2', 'ueadata3', 'ueadata4', 'ueadata5', 'ueadata6', 'ueadata7', 'ueadata8'), repos='<>')'. The installation takes a couple of minutes but we strongly encourage the users to do it if they want to have available all datasets of mlmts. Practitioners from a broad variety of fields could benefit from the general framework provided by 'mlmts'.

Version: 1.1.1
Depends: R (≥ 4.0.0)
Imports: quantspec, waveslim, Rfast, TSclust, forecast, tseries, TSA, tsfeatures, tseriesChaos, freqdom, e1071, dtw, base, psych, complexplus, MTS, Matrix, ggplot2, multiwave, MASS, fda.usc, TSdist, geigen, DescTools, pracma, pspline, Rdpack, stats, ClusterR, AID, caret, ranger, igraph, randomForest
Suggests: ueadata1, ueadata2, ueadata3, ueadata4, ueadata5, ueadata6, ueadata7, ueadata8, testthat (≥ 3.0.0)
Published: 2023-01-22
DOI: 10.32614/CRAN.package.mlmts
Author: Angel Lopez-Oriona [aut, cre], Jose A. Vilar [aut]
Maintainer: Angel Lopez-Oriona <oriona38 at>
License: GPL-2
NeedsCompilation: no
CRAN checks: mlmts results


Reference manual: mlmts.pdf


Package source: mlmts_1.1.1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): mlmts_1.1.1.tgz, r-oldrel (arm64): mlmts_1.1.1.tgz, r-release (x86_64): mlmts_1.1.1.tgz, r-oldrel (x86_64): mlmts_1.1.1.tgz
Old sources: mlmts archive


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