Introduction | Basic concepts | Module references | Python documentation | Importing data for direct handling by python functions | Dimension reduction with sklearn: illustration with iris dataset | PCA | Incremental PCA | Manual incremental PCA with explicit chunking | Interoperation with HDF5 matrix | How to expand scope of BiocSklearn | Conclusions
Package: BiocSklearn 1.35.0
Vince Carey
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_1.35.0.tar.gz
BiocSklearn_1.35.0.zip(r-4.7)BiocSklearn_1.35.0.zip(r-4.6)BiocSklearn_1.35.0.zip(r-4.5)
BiocSklearn_1.35.0.tgz(r-4.6-any)BiocSklearn_1.35.0.tgz(r-4.5-any)
BiocSklearn_1.35.0.tar.gz(r-4.7-any)BiocSklearn_1.35.0.tar.gz(r-4.6-any)
BiocSklearn_1.35.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
BiocSklearn/json (API)
| # Install 'BiocSklearn' in R: |
| install.packages('BiocSklearn', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org')) |
On BioConductor:BiocSklearn-1.35.0(bioc 3.24)BiocSklearn-1.34.0(bioc 3.23)
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
statisticalmethoddimensionreductioninfrastructure
Last updated from:bdbd85915a. Checks:1 WARNING, 9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| bioc-checks | WARNING | 195 | ||
| linux-devel-x86_64 | OK | 1199 | ||
| source / vignettes | OK | 1159 | ||
| linux-release-x86_64 | OK | 1144 | ||
| macos-release-arm64 | OK | 518 | ||
| macos-oldrel-arm64 | OK | 505 | ||
| windows-devel | OK | 247 | ||
| windows-release | OK | 282 | ||
| windows-oldrel | OK | 271 | ||
| wasm-release | OK | 156 |
Exports:getTransformedh5matH5matrefSkDecompskIncrPartialPCAskIncrPCAskIncrPCA_h5skIncrPPCAskKMeansskPartialPCA_stepskPCAskPWD
Dependencies:abindbasiliskBiobaseBiocGenericsDelayedArraydir.expiryfilelockgenericsGenomicRangeshereIRangesjsonlitelatticeMatrixMatrixGenericsmatrixStatspngrappdirsRcppRcppTOMLreticulaterlangrprojrootS4ArraysS4VectorsSeqinfoSparseArraySummarizedExperimentwithrXVector
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 |
