{ "_id": "6a229ceccd65a98ecbd57ccf", "Package": "tools4uplift", "Version": "1.0.1", "Date": "2022-01-10", "Title": "Tools for Uplift Modeling", "Author": "Mouloud Belbahri, Olivier Gandouet, Alejandro Murua, Vahid\nPartovi Nia", "Maintainer": "Mouloud Belbahri ", "Description": "Uplift modeling aims at predicting the causal effect of an\naction such as a marketing campaign on a particular individual.\nIn order to simplify the task for practitioners in uplift\nmodeling, we propose a combination of tools that can be\nseparated into the following ingredients: i) quantization, ii)\nvisualization, iii) variable selection, iv) parameters\nestimation and, v) model validation. For more details, please\nread \"Belbahri, Murua, Gandouet, Partovi Nia - Uplift\nRegression : The R Package tools4uplift\".", "License": "GPL-2 | GPL-3", "Config/pak/sysreqs": "libjpeg-dev libpng-dev", "Repository": "https://belbahrim.r-universe.dev", "Date/Publication": "2022-01-11 16:58:39 UTC", "RemoteUrl": "https://github.com/belbahrim/tools4uplift", "RemoteRef": "HEAD", "RemoteSha": "96d5ca0dbae7de572b62cec53161cdd41df5b578", "NeedsCompilation": "no", "Packaged": { "Date": "2026-06-05 09:51:00 UTC", "User": "root" }, "MD5sum": "14e3c61d006d28f459c2357c5c252c8f", "_user": "belbahrim", "_type": "src", "_file": "tools4uplift_1.0.1.tar.gz", "_fileid": "9a68f147091153fb9e7e867dde15d757f97ce6f011f78cf5354c6135191a3745", "_filesize": 314041, "_sha256": "9a68f147091153fb9e7e867dde15d757f97ce6f011f78cf5354c6135191a3745", "_created": "2026-06-05T09:51:00.000Z", "_published": "2026-06-05T09:54:52.236Z", "_distro": "noble", "_jobs": [ { "job": 79704458203, "time": 151, "config": 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"Suggests" } ], "_owner": "belbahrim", "_selfowned": true, "_usedby": 0, "_updates": [], "_tags": [], "_stars": 0, "_contributors": [ { "user": "belbahrim", "count": 71, "uuid": 32884719 } ], "_userbio": { "uuid": 32884719, "type": "user", "name": "Mouloud Belbahri", "description": "Machine Learning Scientist" }, "_downloads": { "count": 257, "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/tools4uplift" }, "_devurl": "https://github.com/belbahrim/tools4uplift", "_searchresults": 76, "_rbuild": "4.6.0", "_assets": [ "extra/citation.cff", "extra/citation.html", "extra/citation.json", "extra/citation.txt", "extra/contents.json", "extra/readme.html", "extra/readme.md", "extra/tools4uplift.html", "manual.pdf" ], "_homeurl": "https://github.com/belbahrim/tools4uplift", "_realowner": "belbahrim", "_cranurl": true, "_releases": [ { "version": "0.1-0", "date": "2019-01-09" }, { "version": "0.1-1", "date": "2019-01-29" }, { "version": "1.0.0", "date": "2021-01-06" } ], 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{ "page": "BinUplift2d", "title": "Bivariate quantization", "topics": [ "BinUplift2d" ] }, { "page": "DualUplift", "title": "Two-model estimator", "topics": [ "DualUplift", "DualUplift.default", "DualUplift.formula", "print.DualUplift", "summary.DualUplift" ] }, { "page": "InterUplift", "title": "Interaction estimator", "topics": [ "InterUplift", "InterUplift.default", "InterUplift.formula" ] }, { "page": "LassoPath", "title": "LASSO path for the penalized logistic regression", "topics": [ "LassoPath" ] }, { "page": "lines.PerformanceUplift", "title": "Qini curve", "topics": [ "lines.PerformanceUplift" ] }, { "page": "PerformanceUplift", "title": "Performance of an uplift estimator", "topics": [ "PerformanceUplift", "print.PerformanceUplift" ] }, { "page": "plot.PerformanceUplift", "title": "Qini curve", "topics": [ "plot.PerformanceUplift" ] }, { "page": "predict.BinUplift", "title": "Prediction from univariate quantization", "topics": [ "predict.BinUplift" ] }, { "page": 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