Package: mlr3fda 0.2.0
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_0.2.0.tar.gz
mlr3fda_0.2.0.zip(r-4.5)mlr3fda_0.2.0.zip(r-4.4)mlr3fda_0.2.0.zip(r-4.3)
mlr3fda_0.2.0.tgz(r-4.4-any)mlr3fda_0.2.0.tgz(r-4.3-any)
mlr3fda_0.2.0.tar.gz(r-4.5-noble)mlr3fda_0.2.0.tar.gz(r-4.4-noble)
mlr3fda_0.2.0.tgz(r-4.4-emscripten)mlr3fda_0.2.0.tgz(r-4.3-emscripten)
mlr3fda.pdf |mlr3fda.html✨
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
data-analysisdata-analysis-in-rdata-sciencefunctional-datamachine-learningmlr3
Last updated 4 months agofrom:42cd10c77d (on v0.2.0). Checks:OK: 7. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 18 2024 |
R-4.5-win | OK | Nov 18 2024 |
R-4.5-linux | OK | Nov 18 2024 |
R-4.4-win | OK | Nov 18 2024 |
R-4.4-mac | OK | Nov 18 2024 |
R-4.3-win | OK | Nov 18 2024 |
R-4.3-mac | OK | Nov 18 2024 |
Exports:PipeOpFDACorPipeOpFDAExtractPipeOpFDAFlattenPipeOpFDAInterpolPipeOpFDAScaleRangePipeOpFDASmoothPipeOpFPCA
Dependencies:backportscheckmateclicodetoolsdata.tabledigestevaluatefuturefuture.applyglobalsgluelatticelgrlifecyclelistenvmagrittrMatrixmgcvmlbenchmlr3mlr3measuresmlr3miscmlr3pipelinesmvtnormnlmepalmerpenguinsparadoxparallellypracmaPRROCpurrrR6rlangtfuuidvctrswithrzoo
Readme and manuals
Help Manual
Help page | Topics |
---|---|
mlr3fda: Extending 'mlr3' to Functional Data Analysis | mlr3fda-package mlr3fda |
Cross-Correlation of Functional Data | mlr_pipeops_fda.cor PipeOpFDACor |
Extracts Simple Features from Functional Columns | mlr_pipeops_fda.extract PipeOpFDAExtract |
Flattens Functional Columns | mlr_pipeops_fda.flatten PipeOpFDAFlatten |
Functional Principal Component Analysis | mlr_pipeops_fda.fpca PipeOpFPCA |
Interpolate Functional Columns | mlr_pipeops_fda.interpol PipeOpFDAInterpol |
Linearly Transform the Domain of Functional Data. | mlr_pipeops_fda.scalerange PipeOpFDAScaleRange |
Smoothing Functional Columns | mlr_pipeops_fda.smooth PipeOpFDASmooth |
Diffusion Tensor Imaging (DTI) Regression Task | mlr_tasks_dti |
Fuel Regression Task | mlr_tasks_fuel |
Phoneme Classification Task | mlr_tasks_phoneme |