Package: themis 1.0.3.9000
Emil Hvitfeldt
themis: Extra Recipes Steps for Dealing with Unbalanced Data
A dataset with an uneven number of cases in each class is said to be unbalanced. Many models produce a subpar performance on unbalanced datasets. A dataset can be balanced by increasing the number of minority cases using SMOTE 2011 <doi:10.48550/arXiv.1106.1813>, BorderlineSMOTE 2005 <doi:10.1007/11538059_91> and ADASYN 2008 <https://ieeexplore.ieee.org/document/4633969>. Or by decreasing the number of majority cases using NearMiss 2003 <https://www.site.uottawa.ca/~nat/Workshop2003/jzhang.pdf> or Tomek link removal 1976 <https://ieeexplore.ieee.org/document/4309452>.
Authors:
themis_1.0.3.9000.tar.gz
themis_1.0.3.9000.zip(r-4.7)themis_1.0.3.9000.zip(r-4.6)themis_1.0.3.9000.zip(r-4.5)
themis_1.0.3.9000.tgz(r-4.6-any)themis_1.0.3.9000.tgz(r-4.5-any)
themis_1.0.3.9000.tar.gz(r-4.7-any)themis_1.0.3.9000.tar.gz(r-4.6-any)
themis_1.0.3.9000.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
themis/json (API)
NEWS
| # Install 'themis' in R: |
| install.packages('themis', repos = c('https://tidymodels.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/tidymodels/themis/issues
Pkgdown/docs site:https://themis.tidymodels.org
- circle_example - Synthetic Dataset With a Circle
Last updated from:76cf8d0add. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 191 | ||
| source / vignettes | OK | 197 | ||
| linux-release-x86_64 | OK | 224 | ||
| macos-release-arm64 | OK | 123 | ||
| macos-oldrel-arm64 | OK | 287 | ||
| windows-devel | OK | 155 | ||
| windows-release | OK | 131 | ||
| windows-oldrel | OK | 146 | ||
| wasm-release | OK | 117 |
Exports:adasynbsmotenearmissrequired_pkgsrosesmotesmotencstep_adasynstep_bsmotestep_downsamplestep_nearmissstep_rosestep_smotestep_smotencstep_tomekstep_upsampletidytomektunable
Dependencies:classcliclockcodetoolscpp11data.tablediagramdigestdplyrfarverfuturefuture.applygenericsggplot2globalsgluegowergtablehardhatipredisobandKernSmoothlabelinglatticelavalifecyclelistenvlubridatemagrittrMASSMatrixnnetnumDerivparallellypillarpkgconfigprodlimprogressrpurrrR6RANNRColorBrewerRcpprecipesrlangROSErpartS7scalesshapesparsevctrsSQUAREMstringistringrsurvivaltibbletidyrtidyselecttimechangetimeDatetzdbutf8vctrsviridisLitewithr
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Adaptive Synthetic Algorithm | adasyn |
| borderline-SMOTE Algorithm | bsmote |
| Synthetic Dataset With a Circle | circle_example |
| Remove Points Near Other Classes | nearmiss |
| ROSE Algorithm | rose |
| SMOTE Algorithm | smote |
| SMOTENC Algorithm | smotenc |
| Apply Adaptive Synthetic Algorithm | step_adasyn tidy.step_adasyn |
| Apply borderline-SMOTE Algorithm | step_bsmote tidy.step_bsmote |
| Down-Sample a Data Set Based on a Factor Variable | step_downsample tidy.step_downsample |
| Remove Points Near Other Classes | step_nearmiss tidy.step_nearmiss |
| Apply ROSE Algorithm | step_rose tidy.step_rose |
| Apply SMOTE Algorithm | step_smote tidy.step_smote |
| Apply SMOTENC algorithm | step_smotenc tidy.step_smotenc |
| Remove Tomek’s Links | step_tomek tidy.step_tomek |
| Up-Sample a Data Set Based on a Factor Variable | step_upsample tidy.step_upsample |
| Remove Tomek's links | tomek |
