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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: |
0.1.1 |
| Depends: |
mlr3 (≥ 0.14.0), R (≥ 3.1.0) |
| Imports: |
checkmate, data.table, lgr, mlr3misc (≥ 0.14.0), mlr3pipelines, paradox, R6, tf |
| Suggests: |
rpart, testthat (≥ 3.0.0), zoo |
| Published: |
2024-04-09 |
| Author: |
Sebastian Fischer 
[aut, cre],
Maximilian Muecke
[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 |
| CRAN checks: |
mlr3fda results |
Documentation:
Downloads:
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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