mlr3fda: Extending 'mlr3' to Functional Data Analysis

Extends the 'mlr3' ecosystem to functional analysis by adding support for irregular and regular functional data as defined in the 'tf' package. The package provides 'PipeOps' for preprocessing functional columns and for extracting scalar features, thereby allowing standard machine learning algorithms to be applied afterwards. Available operations include simple functional features such as the mean or maximum, smoothing, interpolation, flattening, and functional 'PCA'.

Version:	0.2.0
Depends:	mlr3 (≥ 0.14.0), mlr3pipelines (≥ 0.5.2), R (≥ 3.1.0)
Imports:	checkmate, data.table, lgr, mlr3misc (≥ 0.14.0), paradox, R6, tf (≥ 0.3.4)
Suggests:	rpart, testthat (≥ 3.0.0), withr
Published:	2024-07-22
DOI:	10.32614/CRAN.package.mlr3fda
Author:	Sebastian Fischer [aut, cre], Maximilian Mücke [aut], Fabian Scheipl [ctb], Bernd Bischl [ctb]
Maintainer:	Sebastian Fischer <sebf.fischer at gmail.com>
BugReports:	https://github.com/mlr-org/mlr3fda/issues
License:	LGPL-3
URL:	https://mlr3fda.mlr-org.com, https://github.com/mlr-org/mlr3fda
NeedsCompilation:	no
Materials:	README NEWS
In views:	FunctionalData
CRAN checks:	mlr3fda results

Documentation:

Reference manual:

mlr3fda.pdf

Downloads:

Package source:	mlr3fda_0.2.0.tar.gz
Windows binaries:	r-devel: mlr3fda_0.2.0.zip, r-release: mlr3fda_0.2.0.zip, r-oldrel: mlr3fda_0.2.0.zip
macOS binaries:	r-release (arm64): mlr3fda_0.2.0.tgz, r-oldrel (arm64): mlr3fda_0.2.0.tgz, r-release (x86_64): mlr3fda_0.2.0.tgz, r-oldrel (x86_64): mlr3fda_0.2.0.tgz
Old sources:	mlr3fda archive

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