Package: BiocSklearn 1.29.0
BiocSklearn: interface to python sklearn via Rstudio reticulate
This package provides interfaces to selected sklearn elements, and demonstrates fault tolerant use of python modules requiring extensive iteration.
Authors:
BiocSklearn_1.29.0.tar.gz
BiocSklearn_1.29.0.zip(r-4.5)BiocSklearn_1.29.0.zip(r-4.4)BiocSklearn_1.29.0.zip(r-4.3)
BiocSklearn_1.29.0.tgz(r-4.4-any)BiocSklearn_1.29.0.tgz(r-4.3-any)
BiocSklearn_1.29.0.tar.gz(r-4.5-noble)BiocSklearn_1.29.0.tar.gz(r-4.4-noble)
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BiocSklearn.pdf |BiocSklearn.html✨
BiocSklearn/json (API)
NEWS
# Install 'BiocSklearn' in R: |
install.packages('BiocSklearn', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org')) |
On BioConductor:BiocSklearn-1.27.2(bioc 3.20)BiocSklearn-1.26.1(bioc 3.19)
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
statisticalmethoddimensionreductioninfrastructure
Last updated 22 days agofrom:8c69d92d52. Checks:OK: 7. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Oct 30 2024 |
R-4.5-win | OK | Oct 30 2024 |
R-4.5-linux | OK | Oct 30 2024 |
R-4.4-win | OK | Oct 30 2024 |
R-4.4-mac | OK | Oct 30 2024 |
R-4.3-win | OK | Oct 30 2024 |
R-4.3-mac | OK | Oct 30 2024 |
Exports:getTransformedh5matH5matrefSkDecompskIncrPartialPCAskIncrPCAskIncrPCA_h5skIncrPPCAskKMeansskPartialPCA_stepskPCAskPWD
Dependencies:abindaskpassbasiliskbasilisk.utilsBiobaseBiocGenericscrayoncurlDelayedArraydir.expiryfilelockGenomeInfoDbGenomeInfoDbDataGenomicRangesherehttrIRangesjsonlitelatticeMatrixMatrixGenericsmatrixStatsmimeopensslpngR6rappdirsRcppRcppTOMLreticulaterlangrprojrootS4ArraysS4VectorsSparseArraySummarizedExperimentsysUCSC.utilswithrXVectorzlibbioc
Readme and manuals
Help Manual
Help page | Topics |
---|---|
create a file connection to HDF5 matrix | h5mat |
obtain an HDF5 dataset reference suitable for handling as numpy matrix | H5matref |
constructor for SkDecomp | SkDecomp |
container for sklearn objects and transforms | getTransformed getTransformed,SkDecomp-method SkDecomp-class |
use basilisk discipline to perform partial (n_components) incremental (chunk.size) PCA with scikit.decomposition | skIncrPartialPCA |
use sklearn IncrementalPCA procedure | skIncrPCA |
demo of HDF5 processing with incremental PCA/batch_size/fit_transform | skIncrPCA_h5 |
optionally fault tolerant incremental partial PCA for projection of samples from SummarizedExperiment | skIncrPPCA skIncrPPCA,SummarizedExperiment-method |
interface to sklearn.cluster.KMeans using basilisk discipline | skKMeans |
take a step in sklearn IncrementalPCA partial fit procedure | skPartialPCA_step |
use sklearn PCA procedure | skPCA |
use sklearn pairwise_distances procedure | skPWD |