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: | 0.3.0 | 
| Depends: | mlr3 (≥ 0.14.0), mlr3pipelines (≥ 0.5.2), R (≥ 4.1.0) | 
| Imports: | checkmate, data.table, lgr, mlr3misc (≥ 0.14.0), paradox, R6, tf (≥ 0.3.4) | 
| Suggests: | FDboost, lme4, mboost, rpart, testthat (≥ 3.2.0), tsfeatures, wavelets, withr | 
| Published: | 2025-10-15 | 
| 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 | 
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