Package: mlr3fda 0.6.0
Maximilian Mücke
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'.
Authors:
mlr3fda_0.6.0.tar.gz
mlr3fda_0.6.0.zip(r-4.7)mlr3fda_0.6.0.zip(r-4.6)mlr3fda_0.6.0.zip(r-4.5)
mlr3fda_0.6.0.tgz(r-4.6-any)mlr3fda_0.6.0.tgz(r-4.5-any)
mlr3fda_0.6.0.tar.gz(r-4.7-any)mlr3fda_0.6.0.tar.gz(r-4.6-any)
mlr3fda_0.6.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
mlr3fda/json (API)
NEWS
| # Install 'mlr3fda' in R: |
| install.packages('mlr3fda', repos = c('https://mlr-org.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/mlr-org/mlr3fda/issues
Pkgdown/docs site:https://mlr3fda.mlr-org.com
data-analysisdata-analysis-in-rdata-sciencefunctional-datamachine-learningmlr3
Last updated from:2c3b25041b (on v0.6.0). Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 240 | ||
| source / vignettes | OK | 214 | ||
| linux-release-x86_64 | OK | 241 | ||
| macos-release-arm64 | OK | 155 | ||
| macos-oldrel-arm64 | OK | 185 | ||
| windows-devel | OK | 219 | ||
| windows-release | OK | 195 | ||
| windows-oldrel | OK | 206 | ||
| wasm-release | OK | 122 |
Exports:PipeOpFDABsignalPipeOpFDACorPipeOpFDADepthPipeOpFDADerivePipeOpFDAExtractPipeOpFDAFlattenPipeOpFDAFourierPipeOpFDAInterpolPipeOpFDARandomEffectPipeOpFDARegisterPipeOpFDAScaleRangePipeOpFDASmoothPipeOpFDATsfeaturesPipeOpFDAWaveletsPipeOpFDAZoomPipeOpFPCA
Dependencies:backportscheckmateclicodetoolsdata.tabledigestevaluatefuturefuture.applyglobalsgluelatticelgrlifecyclelistenvmagrittrMatrixmgcvmiraimlbenchmlr3mlr3measuresmlr3miscmlr3pipelinesmvtnormnanonextnlmepalmerpenguinsparadoxparallellypracmaPRROCpurrrR6rlangtfuuidvctrszoo
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| mlr3fda: Extending 'mlr3' to Functional Data Analysis | mlr3fda-package mlr3fda |
| B-spline Feature Extraction | mlr_pipeops_fda.bsignal PipeOpFDABsignal |
| Cross-Correlation of Functional Data | mlr_pipeops_fda.cor PipeOpFDACor |
| Functional Data Depth Features | mlr_pipeops_fda.depth PipeOpFDADepth |
| Derivatives of Functional Columns | mlr_pipeops_fda.derive PipeOpFDADerive |
| Extract Simple Features from Functional Columns | mlr_pipeops_fda.extract PipeOpFDAExtract |
| Flatten Functional Columns | mlr_pipeops_fda.flatten PipeOpFDAFlatten |
| Fast Fourier Transform Features | mlr_pipeops_fda.fourier PipeOpFDAFourier |
| Functional Principal Component Analysis | mlr_pipeops_fda.fpca PipeOpFPCA |
| Interpolate Functional Columns | mlr_pipeops_fda.interpol PipeOpFDAInterpol |
| Extract Random Effects from Functional Columns | mlr_pipeops_fda.random_effect PipeOpFDARandomEffect |
| Register (Align) Functional Columns | mlr_pipeops_fda.register PipeOpFDARegister |
| Linearly Transform the Domain of Functional Data | mlr_pipeops_fda.scalerange PipeOpFDAScaleRange |
| Smooth Functional Columns | mlr_pipeops_fda.smooth PipeOpFDASmooth |
| Time Series Feature Extraction | mlr_pipeops_fda.tsfeats PipeOpFDATsfeatures |
| Discrete Wavelet Transform Features | mlr_pipeops_fda.wavelets PipeOpFDAWavelets |
| Zoom In/Out on Functional Columns | mlr_pipeops_fda.zoom PipeOpFDAZoom |
| Diffusion Tensor Imaging (DTI) Regression Task | mlr_tasks_dti |
| Fuel Regression Task | mlr_tasks_fuel |
| Phoneme Classification Task | mlr_tasks_phoneme |
