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-4.5)tools4uplift_1.0.1.zip(r-4.4)tools4uplift_1.0.1.zip(r-4.3)
tools4uplift_1.0.1.tgz(r-4.4-any)tools4uplift_1.0.1.tgz(r-4.3-any)
tools4uplift_1.0.1.tar.gz(r-4.5-noble)tools4uplift_1.0.1.tar.gz(r-4.4-noble)
tools4uplift_1.0.1.tgz(r-4.4-emscripten)tools4uplift_1.0.1.tgz(r-4.3-emscripten)
tools4uplift.pdf |tools4uplift.html✨
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 3 years agofrom:96d5ca0dba. Checks:OK: 1 WARNING: 6. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 05 2024 |
R-4.5-win | WARNING | Nov 05 2024 |
R-4.5-linux | WARNING | Nov 05 2024 |
R-4.4-win | WARNING | Nov 05 2024 |
R-4.4-mac | WARNING | Nov 05 2024 |
R-4.3-win | WARNING | Nov 05 2024 |
R-4.3-mac | WARNING | Nov 05 2024 |
Exports:barplot.PerformanceUpliftBestFeaturesBinUpliftBinUplift2dDualUpliftInterUpliftLassoPathlines.PerformanceUpliftPerformanceUpliftplot.PerformanceUpliftpredict.BinUpliftpredict.DualUpliftpredict.InterUpliftQiniAreaqLHSSplitUpliftUpliftPerCat
Dependencies:BiasedUrnclicodetoolsdeldirdplyrfansiforeachgenericsglmnetglueinterpiteratorsjpeglatticelatticeExtralhslifecyclemagrittrMASSMatrixpillarpkgconfigpngR6RColorBrewerRcppRcppEigenrlangshapesurvivaltibbletidyselectutf8vctrswithr
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 |