Package: kfold 0.1.1
Dongdong Kong
kfold: Machine Learning for Runoff Prediction
Machine learning In k-fold cross validation .
Authors:
kfold_0.1.1.tar.gz
kfold_0.1.1.zip(r-4.7)kfold_0.1.1.zip(r-4.6)kfold_0.1.1.zip(r-4.5)
kfold_0.1.1.tgz(r-4.6-any)kfold_0.1.1.tgz(r-4.5-any)
kfold_0.1.1.tar.gz(r-4.7-any)kfold_0.1.1.tar.gz(r-4.6-any)
kfold_0.1.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
kfold/json (API)
| # Install 'kfold' in R: |
| install.packages('kfold', repos = c('https://rpkgs.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/rpkgs/kfold/issues
Last updated from:0c74a49e98. Checks:7 WARNING, 2 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | WARNING | 168 | ||
| source / vignettes | OK | 200 | ||
| linux-release-x86_64 | WARNING | 173 | ||
| macos-release-arm64 | WARNING | 106 | ||
| macos-oldrel-arm64 | WARNING | 97 | ||
| windows-devel | WARNING | 133 | ||
| windows-release | WARNING | 129 | ||
| windows-oldrel | WARNING | 122 | ||
| wasm-release | OK | 132 |
Exports:add_previouschunkchunk_stratifiedcv_coeffeature_leadsGOFGOT_listkfold_calibkfold_lmkfold_mlkfold_rfkfold_xgboostmultisessionNSEplanprevious_tn
Dependencies:askpassbase64enccellrangerclassclassIntclicliprcodetoolscpp11crayoncredentialscurldata.tabledescdigestdoParalleldplyre1071foreachfsfstfstcorefurrrfuturegenericsgertgitcredsglobalsgluehmshttr2hydroGOFhydroTSMiniIpaperiteratorsjsonliteKernSmoothlatticelifecyclelistenvlubridatemagrittrMASSMatrixmatrixStatsopensslopenxlsx2parallellypillarpkgconfigplyrprettyunitsprogressproxypurrrqs2R6randomForestrangerrappdirsRcppRcppEigenRcppParallelreadxlrematchremotesrlangrprojrootrstudioapishowtextshowtextdbstringfishstringistringrsvglitesyssysfontssystemfontstextshapingtibbletidyselecttimechangeusethisutf8vctrswhiskerwithrxgboostxtsyamlzeallotzipzoo
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| add_previous | add_previous |
| Stratified k-fold split | chunk_stratified |
| Build lagged feature matrices for multiple lead times | feature_leads |
| Compute GOF across multiple lead-time kfold objects | GOT_list |
| kfold_calib | kfold_calib |
| kfold machine learning | kfold_lm kfold_ml kfold_rf kfold_xgboost |
| GOF | GOF GOF.default GOF.kfold NSE |
| predict for kfold object | predict.kfold |
| previous_tn | previous_tn previous_tn.data.frame previous_tn.default |
