Package: tools4uplift 1.0.1
tools4uplift: Tools for Uplift Modeling
Uplift modeling aims at predicting the causal effect of an action such as a marketing campaign on a particular individual. In order to simplify the task for practitioners in uplift modeling, we propose a combination of tools that can be separated into the following ingredients: i) quantization, ii) visualization, iii) variable selection, iv) parameters estimation and, v) model validation. For more details, please read "Belbahri, Murua, Gandouet, Partovi Nia - Uplift Regression : The R Package tools4uplift".
Authors:
tools4uplift_1.0.1.tar.gz
tools4uplift_1.0.1.zip(r-4.7-any)tools4uplift_1.0.1.zip(r-4.6-any)tools4uplift_1.0.1.zip(r-4.5-any)
tools4uplift_1.0.1.tgz(r-4.6-any)tools4uplift_1.0.1.tgz(r-4.5-any)
tools4uplift_1.0.1.tar.gz(r-4.7-any)tools4uplift_1.0.1.tar.gz(r-4.6-any)
tools4uplift_1.0.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
tools4uplift/json (API)
| # Install 'tools4uplift' in R: |
| install.packages('tools4uplift', repos = c('https://belbahrim.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/belbahrim/tools4uplift/issues
- SimUplift - Synthetic data for uplift modeling
Last updated from:96d5ca0dba. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel | OK | 175 | ||
| source / vignettes | OK | 174 | ||
| linux-release | OK | 134 | ||
| macos-release | OK | 183 | ||
| macos-oldrel | OK | 153 | ||
| windows-devel | OK | 108 | ||
| windows-release | OK | 104 | ||
| windows-oldrel | OK | 81 | ||
| wasm-release | OK | 89 |
Exports:barplot.PerformanceUpliftBestFeaturesBinUpliftBinUplift2dDualUpliftInterUpliftLassoPathlines.PerformanceUpliftPerformanceUpliftplot.PerformanceUpliftpredict.BinUpliftpredict.DualUpliftpredict.InterUpliftQiniAreaqLHSSplitUpliftUpliftPerCat
Dependencies:BiasedUrnclicodetoolsdeldirdplyrforeachgenericsglmnetglueinterpiteratorsjpeglatticelatticeExtralhslifecyclemagrittrMASSMatrixpillarpkgconfigpngR6RColorBrewerRcppRcppEigenrlangshapesurvivaltibbletidyselectutf8vctrswithr
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Uplift barplot | barplot.PerformanceUplift |
| Qini-based feature selection | BestFeatures |
| Univariate quantization | BinUplift |
| Bivariate quantization | BinUplift2d |
| Two-model estimator | DualUplift DualUplift.default DualUplift.formula print.DualUplift summary.DualUplift |
| Interaction estimator | InterUplift InterUplift.default InterUplift.formula |
| LASSO path for the penalized logistic regression | LassoPath |
| Qini curve | lines.PerformanceUplift |
| Performance of an uplift estimator | PerformanceUplift print.PerformanceUplift |
| Qini curve | plot.PerformanceUplift |
| Prediction from univariate quantization | predict.BinUplift |
| Predictions from a two-model estimator | predict.DualUplift |
| Predictions from an interaction estimator | predict.InterUplift |
| Qini coefficient | QiniArea QiniArea.default QiniArea.PerformanceUplift |
| Qini-based uplift regression | qLHS |
| Synthetic data for uplift modeling | SimUplift |
| Split data with respect to uplift distribution | SplitUplift |
| Uplift barplot for categorical variables | UpliftPerCat |