The library allows to perform a multivariate time series classification based on the use of Discrete Wavelet Transform for feature extraction, a step wise discriminant to select the most relevant features and finally, the use of a linear or quadratic discriminant for classification. Note that all these steps can be done separately which allows to implement new steps. Velasco, I., Sipols, A., de Blas, C. S., Pastor, L., & Bayona, S. (2023) <doi:10.1186/S12938-023-01079-X>. Percival, D. B., & Walden, A. T. (2000,ISBN:0521640687). Maharaj, E. A., & Alonso, A. M. (2014) <doi:10.1016/j.csda.2013.09.006>.
Version: 0.1.3 Depends: R (≥ 4.3.0) Imports: bigmemory, caret, checkmate, magrittr, MASS, methods, parallel, parallelly, pryr, statcomp, stats, synchronicity, utils, waveslim, wdm Suggests: spelling, testthat (≥ 3.0.0) Published: 2024-07-02 DOI: 10.32614/CRAN.package.TSEAL Author: Iván Velasco [aut, cre, cph] Maintainer: Iván Velasco <ivan.velasco at urjc.es> BugReports: https://github.com/vg-lab/TSEAL/issues License: Artistic-2.0 URL: https://github.com/vg-lab/TSEAL NeedsCompilation: no Language: en-US In views: TimeSeries CRAN checks: TSEAL results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=TSEAL to link to this page.
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