{ "_id": "6ac4c79cf511ae58c09a13b1", "Package": "Information", "Type": "Package", "Title": "Data Exploration with Information Theory (Weight-of-Evidence and\nInformation Value)", "Version": "0.0.9", "Date": "2016-04-08", "Authors@R": "person(\"Larsen\", \"Kim\", email = \"kblarsen4@gmail.com\", role = c(\"aut\", \"cre\"))", "Description": "Performs exploratory data analysis and variable screening\nfor binary classification models using weight-of-evidence (WOE)\nand information value (IV). In order to make the package as\nefficient as possible, aggregations are done in data.table and\ncreation of WOE vectors can be distributed across multiple\ncores. 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Provide readable reasons if errors are found.", "topics": [ "CheckInputs" ] }, { "page": "create_infotables", "title": "Create WOE/NWOE tables and rank variables by IV/NIV", "topics": [ "create_infotables" ] }, { "page": "Information", "title": "Data exploration with information theory (weight-of-evidence and information value)", "topics": [ "Information-package", "Information" ] }, { "page": "is.binary", "title": "(helper function) Calculate cross validation penalty", "topics": [ "is.binary" ] }, { "page": "MultiPlot", "title": "(helper function) Plot mutiple WOE vectors on one page", "topics": [ "MultiPlot" ] }, { "page": "NWOE", "title": "Create WOE table (helper function)", "topics": [ "NWOE" ] }, { "page": "penalty", "title": "(helper function) Calculate cross validation penalty", "topics": [ "penalty" ] }, { "page": "plot_infotables", "title": "Create bar charts for WOE or NWOE vectors", "topics": [ "plot_infotables" ] }, { "page": "SinglePlot", "title": "(helper function) Plot a WOE or NWOE vector", "topics": [ "SinglePlot" ] }, { "page": "train", "title": "Training dataset", "topics": [ "train" ] }, { "page": "valid", "title": "Validation dataset", "topics": [ "valid" ] }, { "page": "WOE", "title": "Create WOE tables from aggregated data (helper function)", "topics": [ "WOE" ] } ], "_readme": "https://github.com/klarsen1/information/raw/HEAD/README.md", "_rundeps": [ "cli", "codetools", "cpp11", "data.table", "doParallel", "farver", "foreach", "ggplot2", "glue", "gtable", "isoband", "iterators", "labeling", "lifecycle", "plyr", "R6", "RColorBrewer", "Rcpp", "rlang", "S7", "scales", "vctrs", "viridisLite", "withr" ], "_vignettes": [ { "source": "Information-vignette.Rmd", "filename": "Information-vignette.html", "title": "Information Package Vignette", "author": "Kim Larsen", "engine": "knitr::rmarkdown_notangle", "headings": [ "Introduction", "Information Theory", "Defining WOE and IV", "The Weight of Evidence", "Ties to Naive Bayes and Logistic Regression", "The Information Value", "Estimating WOE", "Extensions to Exploratory Analysis for Uplift Models", "The Information R Package", "Data Used in Examples", "Key Functions", "External Cross Validation", "Example for a Traditional Binary Classification Problem", "Ranking All Variables Using Adjusted IV", "Analyzing WOE Patterns", "Plotting WOE Patterns", "Omitting Cross Validation", "Changing the Number of Bins", "Uplift Example", "Combining IV Analysis With Variable Clustering", "Summary", "References", "Other Packages that support information theory" ], "created": "2015-09-12 01:30:07", "modified": "2015-11-18 21:52:05", "commits": 8 } ], "_score": 7.491641793477586, "_indexed": true, "_nocasepkg": "information", "_universes": [ "klarsen1" ], "_binaries": [ { "r": "4.7.0", "os": "linux", "version": "0.0.9", "date": "2026-10-06T10:02:12.000Z", "distro": "resolute", "commit": "b3a826a6f8a38aa8c664156cef4f16edae196ec3", "fileid": 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