{ "_id": "6a1be8b11d7bb097a0a1c3a5", "Package": "LogisticEnsembles", "Type": "Package", "Title": "Automatically Runs 18 Logistic Models-14 Individual Logistic\nModels and 4 Ensembles of Models", "Version": "1.0.2.9000", "Authors@R": "person(\"Russ\", \"Conte\", , \"russconte@mac.com\", role = c(\"aut\", \"cre\", \"cph\"))", "Description": "Automatically returns results from 18 logistic models\nincluding 14 individual logistic models and 4 logistic\nensembles of models. The package also returns 25 plots, 5\ntables, and a summary report. The package automatically builds\nall 18 models, reports all results, and provides graphics to\nshow how the models performed. This can be used for a wide\nrange of data, such as sports or medical data. The package\nincludes medical data (the Pima Indians data set), and\ninformation about the performance of Lebron James. The package\ncan be used to analyze many other examples, such as stock\nmarket data. The package automatically returns many values for\neach model, such as True Positive Rate, True Negative Rate,\nFalse Positive Rate, False Negative Rate, Positive Predictive\nValue, Negative Predictive Value, F1 Score, Area Under the\nCurve. The package also returns 36 Receiver Operating\nCharacteristic (ROC) curves for each of the 18 models.", "License": "MIT + file LICENSE", "Encoding": "UTF-8", "LazyData": "true", "RoxygenNote": "7.3.3", "VignetteBuilder": "knitr", "URL": "https://github.com/InfiniteCuriosity/LogisticEnsembles", "BugReports": "https://github.com/InfiniteCuriosity/LogisticEnsembles/issues", "Config/pak/sysreqs": "cmake make libicu-dev libuv1-dev libxml2-dev\nlibssl-dev libnode-dev libx11-dev zlib1g-dev", "Repository": "https://infinitecuriosity.r-universe.dev", "Date/Publication": "2026-04-01 16:55:10 UTC", "RemoteUrl": "https://github.com/infinitecuriosity/logisticensembles", "RemoteRef": "HEAD", "RemoteSha": "c0e1845be78fa536aa016fef86382cdeb4060411", "NeedsCompilation": "no", "Packaged": { "Date": "2026-05-31 07:08:53 UTC", "User": "root" }, "Author": "Russ Conte [aut, cre, cph]", "Maintainer": "Russ Conte ", "MD5sum": "b9944f27c93be5f58e5ca152a9cada39", "_user": "infinitecuriosity", "_type": "src", "_file": "LogisticEnsembles_1.0.2.9000.tar.gz", "_fileid": "9e2a204f9251dc335c4256e024035321723d8b8116281e0349e0989ad33b0b67", "_filesize": 4281531, "_sha256": "9e2a204f9251dc335c4256e024035321723d8b8116281e0349e0989ad33b0b67", "_created": "2026-05-31T07:08:53.000Z", "_published": "2026-05-31T07:52:17.762Z", "_distro": "noble", "_jobs": [ { "job": 78707696295, "time": 271, "config": "linux-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "7314708278" }, { "job": 78707696298, "time": 260, "config": "linux-release-x86_64", "r": "4.6.0", "check": "OK", "artifact": "7314706928" }, { "job": 78707696292, "time": 202, "config": "macos-oldrel-arm64", "r": "4.5.3", "check": "OK", "artifact": "7314971267" }, { "job": 78707696305, "time": 180, "config": "macos-release-arm64", "r": "4.6.0", "check": "OK", "artifact": "7314977221" }, { "job": 78707429562, "time": 290, "config": "source", "r": "4.6.0", "check": "OK", "artifact": "7314679084" }, { "job": 78707696301, "time": 162, "config": "wasm-release", "r": "4.6.0", "check": "OK", "artifact": "7314695803" }, { "job": 78707696288, "time": 191, "config": "windows-devel", "r": "4.7.0", "check": "OK", "artifact": "7314699186" }, { "job": 78707696290, "time": 193, "config": "windows-oldrel", "r": "4.5.3", "check": "OK", "artifact": "7314699312" }, { "job": 78707696296, "time": 178, "config": "windows-release", "r": "4.6.0", "check": "OK", "artifact": "7314697597" } ], "_buildurl": "https://github.com/r-universe/infinitecuriosity/actions/runs/26706053768", "_status": "success", "_host": "GitHub-Actions", "_upstream": "https://github.com/infinitecuriosity/logisticensembles", "_commit": { "id": "c0e1845be78fa536aa016fef86382cdeb4060411", "author": "Russ Conte ", "committer": "Russ Conte ", "message": "removed models which are not being used.\n", "time": 1775062510 }, "_maintainer": { "name": "Russ Conte", "email": "russconte@mac.com", "login": "infinitecuriosity", "description": "Looking for ways to contribute and share in Data Science, feel free to contact me!", "uuid": 21028719 }, "_registered": true, "_dependencies": [ { "package": "adabag", "role": "Depends" }, { "package": "arm", "role": "Depends" }, { "package": "brnn", "role": "Depends" }, { "package": "C50", "role": "Depends" }, { "package": "car", "role": "Depends" }, { "package": "caret", "role": "Depends" }, { "package": "corrplot", "role": "Depends" }, { "package": "doParallel", "role": "Depends" }, { "package": "dplyr", "role": "Depends" }, { "package": "e1071", "role": "Depends" }, { "package": "gam", "role": "Depends" }, { "package": "gbm", "role": "Depends" }, { "package": "ggplot2", "role": "Depends" }, { "package": "ggplotify", "role": "Depends" }, { "package": "glmnet", "role": "Depends" }, { "package": "graphics", "role": "Depends" }, { "package": "gridExtra", "role": "Depends" }, { "package": "gt", "role": "Depends" }, { "package": "htmltools", "role": "Depends" }, { "package": "htmlwidgets", "role": "Depends" }, { "package": "ipred", "role": "Depends" }, { "package": "klaR", "role": "Depends" }, { "package": "MachineShop", "role": "Depends" }, { "package": "magrittr", "role": "Depends" }, { "package": "mda", "role": "Depends" }, { "package": "nnet", "role": "Depends" }, { "package": "olsrr", "role": "Depends" }, { "package": "parallel", "role": "Depends" }, { "package": "pls", "role": "Depends" }, { "package": "pROC", "role": "Depends" }, { "package": "purrr", "role": "Depends" }, { "package": "R", "version": ">= 4.1.0", "role": "Depends" }, { "package": "randomForest", "role": "Depends" }, { "package": "ranger", "role": "Depends" }, { "package": "reactable", "role": "Depends" }, { "package": "readr", "role": "Depends" }, { "package": "rpart", "role": "Depends" }, { "package": "scales", "role": "Depends" }, { "package": "stats", "role": "Depends" }, { "package": "tidyr", "role": "Depends" }, { "package": "utils", "role": "Depends" }, { "package": "vip", "role": "Depends" }, { "package": "xgboost", "role": "Depends" }, { "package": "knitr", "role": "Suggests" }, { "package": "rmarkdown", "role": "Suggests" } ], "_owner": "infinitecuriosity", "_selfowned": true, "_usedby": 0, "_updates": [ { "week": "2025-35", "n": 36 }, { "week": "2025-40", "n": 4 }, { "week": "2025-41", "n": 9 }, { "week": "2026-06", "n": 19 }, { "week": "2026-07", "n": 16 }, { "week": "2026-08", "n": 3 }, { "week": "2026-09", "n": 9 }, { "week": "2026-14", "n": 4 } ], "_tags": [ { "name": "v0.8.0", "date": "2025-08-31" }, { "name": "v0.8.1", "date": "2025-08-31" }, { "name": "v1.0.2", "date": "2026-02-26" } ], "_stars": 3, "_contributors": [ { "user": "infinitecuriosity", "count": 127, "uuid": 21028719 } ], "_userbio": { "uuid": 21028719, "type": "user", "name": "Russ Conte", "description": "Looking for ways to contribute and share in Data Science, feel free to contact me!" }, "_downloads": { "count": 231, "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/LogisticEnsembles" }, "_devurl": "https://github.com/infinitecuriosity/logisticensembles", "_searchresults": 11, "_rbuild": "4.6.0", "_assets": [ "extra/citation.cff", "extra/citation.html", "extra/citation.json", "extra/citation.txt", "extra/contents.json", "extra/LogisticEnsembles.html", "extra/NEWS.html", "extra/NEWS.txt", "extra/readme.html", "extra/readme.md", "manual.pdf" ], "_homeurl": "https://github.com/infinitecuriosity/logisticensembles", "_realowner": "infinitecuriosity", "_cranurl": true, "_releases": [ { "version": "0.5.0", "date": "2025-04-01" }, { "version": "0.6.0", "date": "2025-08-24" }, { "version": "0.8.0", "date": "2025-08-31" }, { "version": "0.8.1", "date": "2025-08-31" }, { "version": "0.8.2", "date": "2025-10-12" }, { "version": "1.0.0", "date": "2026-02-16" }, { "version": "1.0.2", "date": "2026-02-26" } ], "_exports": [ "Logistic" ], "_datasets": [ { "name": "Cervical_cancer", "title": "Cervical_cancer-This data set predicts a patient's risk of cervical cancer based on behavior reports", "object": "Cervical_cancer", "class": [ "data.frame" ], "fields": [ "Age", "Number.of.sexual.partners", "First.sexual.intercourse", "Num.of.pregnancies", "Smokes", "Smokes..years.", "Smokes..packs.year.", "Hormonal.Contraceptives", "Hormonal.Contraceptives..years.", "IUD", "IUD..years.", "STDs", "STDs..number.", "STDs.condylomatosis", "STDs.cervical.condylomatosis", "STDs.vaginal.condylomatosis", "STDs.vulvo.perineal.condylomatosis", "STDs.syphilis", "STDs.pelvic.inflammatory.disease", "STDs.genital.herpes", "STDs.molluscum.contagiosum", "STDs.AIDS", "STDs.HIV", "STDs.Hepatitis.B", "STDs.HPV", "STDs..Number.of.diagnosis", "Dx.Cancer", "Dx.CIN", "Dx.HPV", "Dx", "Hinselmann", "Schiller", "Citology", "Biopsy" ], "rows": 858, "table": true, "tojson": true }, { "name": "Diabetes", "title": "Diabetes—A logistic data set, determining whether a woman tested positive for diabetes. 100 percent accurate results are possible using the logistic function in the Ensembles package.", "object": "Diabetes", "class": [ "data.frame" ], "fields": [ "Pregnancies", "Glucose", "BloodPressure", "SkinThickness", "Insulin", "BMI", "DiabetesPedigreeFunction", "Age", "Outcome" ], "rows": 768, "table": true, "tojson": true }, { "name": "German_Credit_Risk", "title": "German_Credit_Risk-This dataset classifies people described by a set of attributes as good or bad credit risks. #'", "object": "German_Credit_Risk", "class": [ "data.frame" ], "fields": [ "Status", "Duration", "Credit_History", "Purpose", "Credit_Amount", "Savings_Accounts", "Present_Employment_Since", "Installment_Rate", "Marital_Status", "Other_Debtors", "Present_Residence_Since", "Property", "Age", "Other_Installment_Plans", "Housing", "Number_of_Credit_Cards", "Job", "Number_of_Dependents", "Telephone", "Foreign_Worker", "Class" ], "rows": 999, "table": true, "tojson": true }, { "name": "Lebron", "title": "Lebron—A logistic data set, with the result indicating whether or not Lebron scored on each shot in the data set.", "object": "Lebron", "class": [ "data.frame" ], "fields": [ "top", "left", "date", "qtr", "time_remaining", "result", "shot_type", "distance_ft", "lead", "lebron_team_score", "opponent_team_score", "opponent" ], "rows": 1533, "table": true, "tojson": true }, { "name": "SAHeart", "title": "SAHeart data", "object": "SAHeart", "class": [ "data.frame" ], "fields": [ "sbp", "tobacco", "ldl", "adiposity", "famhist", "typea", "obesity", "alcohol", "age", "chd" ], "rows": 462, "table": true, "tojson": true } ], "_help": [ { "page": "Cervical_cancer", "title": "Cervical_cancer-This data set predicts a patient's risk of cervical cancer based on behavior reports", "topics": [ "Cervical_cancer" ] }, { "page": "Diabetes", "title": "Diabetes—A logistic data set, determining whether a woman tested positive for diabetes. 100 percent accurate results are possible using the logistic function in the Ensembles package.", "topics": [ "Diabetes" ] }, { "page": "German_Credit_Risk", "title": "German_Credit_Risk-This dataset classifies people described by a set of attributes as good or bad credit risks. #'", "topics": [ "German_Credit_Risk" ] }, { "page": "Lebron", "title": "Lebron—A logistic data set, with the result indicating whether or not Lebron scored on each shot in the data set.", "topics": [ "Lebron" ] }, { "page": "Logistic", "title": "logistic—function to perform logistic analysis and return the results to the user.", "topics": [ "Logistic" ] }, { "page": "SAHeart", "title": "SAHeart data", "topics": [ "SAHeart" ] } ], "_readme": "https://github.com/infinitecuriosity/logisticensembles/raw/HEAD/README.md", "_rundeps": [ "abind", "adabag", "arm", "backports", "base64enc", "bigD", "bit", "bit64", "bitops", "boot", "brnn", "broom", "bslib", "C50", "cachem", "car", "carData", "caret", "class", "classInt", "cli", "clipr", "clock", "coda", "codetools", "coin", "colorspace", "combinat", "commonmark", "ConsRank", "corrplot", "cowplot", "cpp11", "crayon", "Cubist", "curl", "data.table", "Deriv", "diagram", "dials", "DiceDesign", "digest", "doBy", "doParallel", "dplyr", "e1071", "evaluate", "farver", "fastmap", "fontawesome", "forcats", "foreach", "forecast", "Formula", "fracdiff", "fs", "furrr", "future", "future.apply", "gam", "gbm", "generics", "ggplot2", "ggplotify", "glmnet", "globals", "glue", "goftest", "gower", "gridExtra", "gridGraphics", "gt", "gtable", "gtools", "hardhat", "haven", "highr", "hms", "htmltools", "htmlwidgets", "httpuv", "inum", "ipred", "isoband", "iterators", "jquerylib", "jsonlite", "juicyjuice", "kernlab", "KernSmooth", "klaR", "knitr", "labeling", "labelled", "later", "lattice", "lava", "libcoin", "lifecycle", "listenv", "litedown", "lme4", "lmtest", "lubridate", "MachineShop", "magrittr", "markdown", "MASS", "Matrix", "MatrixModels", "matrixStats", "mda", "memoise", "mgcv", "microbenchmark", "mime", "miniUI", "minqa", "ModelMetrics", "modelr", "modeltools", "multcomp", "mvtnorm", "nlme", "nloptr", "nnet", "nortest", "numDeriv", "olsrr", "otel", "parallelly", "party", "partykit", "pbkrtest", "pillar", "pkgconfig", "pls", "plyr", "polspline", "prettyunits", "pROC", "prodlim", "progress", "progressr", "promises", "proxy", "purrr", "quantreg", "questionr", "R.cache", "R.methodsS3", "R.oo", "R.utils", "R6", "randomForest", "ranger", "rappdirs", "rbibutils", "RColorBrewer", "Rcpp", "RcppArmadillo", "RcppEigen", "Rdpack", "reactable", "reactR", "readr", "recipes", "reformulas", "reshape2", "rlang", "rlist", "rmarkdown", "rpart", "rprojroot", "rsample", "Rsolnp", "rstudioapi", "S7", "sandwich", "sass", "scales", "sfd", "shape", "shiny", "slider", "sourcetools", "SparseM", "sparsevctrs", "SQUAREM", "stringi", "stringr", "strucchange", "styler", "survival", "TH.data", "tibble", "tidyr", "tidyselect", "timechange", "timeDate", "tinytex", "truncnorm", "tzdb", "urca", "utf8", "V8", "vctrs", "vip", "viridisLite", "vroom", "warp", "withr", "xfun", "xgboost", "XML", "xml2", "xplorerr", "xtable", "yaml", "yardstick", "yulab.utils", "zoo" ], "_vignettes": [ { "source": "vignette_Report_template.Rmd", "filename": "vignette_Report_template.html", "title": "Logistic report template", "engine": "knitr::rmarkdown", "headings": [ "Introduction", "Statement of the problem from the customer's perspective", "History of the problem, previous results", "Exploratory data analysis", "24 logistic models (Individual models then ensembles, in alphabetical order)", "Ensembles and individual model plots", "Strongest evidence based results:", "Five strongest evidence based recommendations", "Conclusions", "References" ], "created": "2025-10-05 23:11:27", "modified": "2025-10-12 20:45:23", "commits": 4 }, { "source": "vignette_0_The_Hello_World_of_LogisticEnsembles.Rmd", "filename": "vignette_0_The_Hello_World_of_LogisticEnsembles.html", "title": "vignette_0_The_Hello_World_of_LogisticEnsembles", "engine": "knitr::rmarkdown", "headings": [ "Installation", "Example", "24 summary tables (three are shown):", "Summary Report", "Finding the strongest predictor from the most accurate model(s)", "Grand Summary" ], "created": "2025-10-05 23:11:27", "modified": "2026-02-26 20:44:31", "commits": 4 }, { "source": "vignette_1_data_colnum_numresamples.Rmd", "filename": "vignette_1_data_colnum_numresamples.html", "title": "vignette_1_the_data-colnum-numresamples", "engine": "knitr::rmarkdown", "headings": [], "created": "2025-10-05 23:11:27", "modified": "2025-10-12 19:57:33", "commits": 3 }, { "source": "vignette_2_remove_VIF_greater_than.Rmd", "filename": "vignette_2_remove_VIF_greater_than.html", "title": "vignette_2_remove_VIF_greater_than", "engine": "knitr::rmarkdown", "headings": [], "created": "2025-10-05 23:11:27", "modified": "2025-10-12 19:57:33", "commits": 3 }, { "source": "vignette_3_remove_ensemble_correlations_greater_than.Rmd", "filename": "vignette_3_remove_ensemble_correlations_greater_than.html", "title": "vignette_3_remove_ensemble_correlations_greater_than", "engine": "knitr::rmarkdown", "headings": [], "created": "2025-10-05 23:11:27", "modified": "2025-10-12 19:57:33", "commits": 3 }, { "source": "vignette_4_save_all_trained_models_and_plots.Rmd", "filename": "vignette_4_save_all_trained_models_and_plots.html", "title": "vignette_4_save_all_trained_models_and_save_all_plots", "engine": "knitr::rmarkdown", "headings": [], "created": "2025-10-05 23:11:27", "modified": "2025-10-12 19:57:33", "commits": 3 }, { "source": "vignette_5_how_to_handle_strings.Rmd", "filename": "vignette_5_how_to_handle_strings.html", "title": "vignette_5_how_to_handle_strings", "engine": "knitr::rmarkdown", "headings": [], "created": "2025-10-05 23:11:27", "modified": "2025-10-12 19:57:33", "commits": 3 }, { "source": "vignette_6_set_seed.Rmd", "filename": "vignette_6_set_seed.html", "title": "vignette_6_set_seed", "engine": "knitr::rmarkdown", "headings": [], "created": "2025-10-05 23:11:27", "modified": "2025-10-12 19:57:33", "commits": 3 }, { "source": "vignette_7_do_you_have_new_data.Rmd", "filename": "vignette_7_do_you_have_new_data.html", "title": "vignette_7_do_you_have_new_data", "engine": "knitr::rmarkdown", "headings": [], "created": "2025-10-05 23:11:27", "modified": "2025-10-12 19:57:33", "commits": 3 }, { "source": "vignette_8_Capstone_Using_multiple_features.Rmd", "filename": "vignette_8_Capstone_Using_multiple_features.html", "title": "vignette_8_Capstone-Using_multiple_features", "engine": "knitr::rmarkdown", "headings": [], "created": "2025-10-05 23:11:27", "modified": "2025-10-12 19:57:33", "commits": 3 } ], "_score": 6.12057393120585, "_indexed": true, "_nocasepkg": "logisticensembles", "_universes": [ "infinitecuriosity" ], "_binaries": [ { "r": "4.7.0", "os": "linux", "version": "1.0.2.9000", "date": "2026-05-31T07:12:14.000Z", "distro": "noble", "commit": "c0e1845be78fa536aa016fef86382cdeb4060411", "fileid": "6f08338d593123917a60a3431e5f132e2198e87a5b024ee9b6be052a7f9d0b98", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/infinitecuriosity/actions/runs/26706053768" }, { "r": "4.6.0", "os": "linux", "version": "1.0.2.9000", "date": "2026-05-31T07:12:10.000Z", "distro": "noble", "commit": "c0e1845be78fa536aa016fef86382cdeb4060411", "fileid": "0ff5ebf74abb4b60cd0518931990b5d75e6d60eff2924bb05af3828cce75f57c", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/infinitecuriosity/actions/runs/26706053768" }, { "r": "4.5.3", "os": "mac", "version": "1.0.2.9000", "date": "2026-05-31T07:49:25.000Z", "commit": "c0e1845be78fa536aa016fef86382cdeb4060411", "fileid": "6d19c2e300a6125880018bd62c47ae2ca1b9e6e1637bef22032413befd1904bf", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/infinitecuriosity/actions/runs/26706053768" }, { "r": "4.6.0", "os": "mac", "version": "1.0.2.9000", "date": "2026-05-31T07:50:34.000Z", "commit": "c0e1845be78fa536aa016fef86382cdeb4060411", "fileid": "484a4115c1c784e1589f648adef7a16a6d8c61c1d4491ed2cf8ea43d8817422e", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/infinitecuriosity/actions/runs/26706053768" }, { "r": "4.6.0", "os": "wasm", "version": "1.0.2.9000", "date": "2026-05-31T07:12:07.000Z", "commit": "c0e1845be78fa536aa016fef86382cdeb4060411", "fileid": "c0fe4ca170011233ab5e42cba9f8b38ce236c6c848ff751bd8a8fa5fa4f101f7", "status": "success", "buildurl": "https://github.com/r-universe/infinitecuriosity/actions/runs/26706053768" }, { "r": "4.7.0", "os": "win", "version": "1.0.2.9000", "date": "2026-05-31T07:10:38.000Z", "commit": "c0e1845be78fa536aa016fef86382cdeb4060411", "fileid": "18b66d1e8296130b0121d3bdde544277ee55745904e033090784eccda5d3b3c6", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/infinitecuriosity/actions/runs/26706053768" }, { "r": "4.5.3", "os": "win", "version": "1.0.2.9000", "date": "2026-05-31T07:11:08.000Z", "commit": "c0e1845be78fa536aa016fef86382cdeb4060411", "fileid": "96b3411bb7bc7fc295edd9ce15d720c1eb99cc2c09217ad8f2e49449a06481f7", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/infinitecuriosity/actions/runs/26706053768" }, { "r": "4.6.0", "os": "win", "version": "1.0.2.9000", "date": "2026-05-31T07:10:50.000Z", "commit": "c0e1845be78fa536aa016fef86382cdeb4060411", "fileid": "d67851b87cd6557d90c6aaf7a69e15eaf44226fb5851291e1e24c9aa06f84784", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/infinitecuriosity/actions/runs/26706053768" } ] }