Package: mlr3oml 0.12.0

Sebastian Fischer

mlr3oml: Connector Between 'mlr3' and 'OpenML'

Provides an interface to 'OpenML.org' to list and download machine learning data, tasks and experiments. The 'OpenML' objects can be automatically converted to 'mlr3' objects. For a more sophisticated interface with more upload options, see the 'OpenML' package.

Authors:Michel Lang [aut], Sebastian Fischer [cre, aut]

mlr3oml_0.12.0.tar.gz
mlr3oml_0.12.0.zip(r-4.7)mlr3oml_0.12.0.zip(r-4.6)mlr3oml_0.12.0.zip(r-4.5)
mlr3oml_0.12.0.tgz(r-4.6-x86_64)mlr3oml_0.12.0.tgz(r-4.6-arm64)mlr3oml_0.12.0.tgz(r-4.5-x86_64)mlr3oml_0.12.0.tgz(r-4.5-arm64)
mlr3oml_0.12.0.tar.gz(r-4.7-arm64)mlr3oml_0.12.0.tar.gz(r-4.7-x86_64)mlr3oml_0.12.0.tar.gz(r-4.6-arm64)mlr3oml_0.12.0.tar.gz(r-4.6-x86_64)
mlr3oml_0.12.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html
DESCRIPTION |NEWS
card.svg |card.png
mlr3oml/json (API)

# Install 'mlr3oml' in R:
install.packages('mlr3oml', repos = c('https://mlr-org.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/mlr-org/mlr3oml/issues

Pkgdown/docs site:https://mlr3oml.mlr-org.com

Uses libs:
  • c++– GNU Standard C++ Library v3

On CRAN:

Conda:

datadata-sciencedatasetsmachine-learningmlr3openmlcpp

6.55 score 10 stars 135 scripts 3.5k downloads 24 exports 31 dependencies

Last updated from:c0f9691eb9 (on v0.12.0). Checks:13 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK168
linux-devel-x86_64OK194
source / vignettesOK190
linux-release-arm64OK194
linux-release-x86_64OK165
macos-release-arm64OK96
macos-release-x86_64OK234
macos-oldrel-arm64OK106
macos-oldrel-x86_64OK160
windows-develOK117
windows-releaseOK119
windows-oldrelOK108
wasm-releaseOK150

Exports:list_oml_collectionslist_oml_datalist_oml_evaluationslist_oml_flowslist_oml_measureslist_oml_runslist_oml_setupslist_oml_tasksoclodtoflwOMLCollectionOMLDataOMLFlowOMLObjectOMLRunOMLTaskornotskpublish_collectionpublish_datapublish_taskread_arffwrite_arff

Dependencies:backportsbitbit64checkmateclicodetoolscurldata.tabledigestevaluatefuturefuture.applyglobalsjsonlitelgrlistenvmiraimlbenchmlr3mlr3measuresmlr3miscnanonextpalmerpenguinsparadoxparallellyPRROCR6rlangstringiuuidwithr