{ "_id": "6ac77722de46216d5edd04e3", "Package": "mob", "Title": "Monotonic Optimal Binning", "Version": "0.4.2", "Description": "Generate the monotonic binning and perform the woe (weight\nof evidence) transformation for the logistic regression used in\nthe consumer credit scorecard development. The woe\ntransformation is a piecewise transformation that is linear to\nthe log odds. For a numeric variable, all of its monotonic\nfunctional transformations will converge to the same woe\ntransformation.", "License": "GPL (>= 2)", "URL": "https://github.com/statcompute/mob", "Author": "WenSui Liu", "Maintainer": "WenSui Liu ", "Encoding": "UTF-8", "LazyData": "true", "RoxygenNote": "7.1.1", "NeedsCompilation": "no", "Packaged": { "Date": "2026-10-08 10:01:17 UTC", "User": "root" }, "Repository": "https://statcompute.r-universe.dev", "Date/Publication": "2021-07-31 03:30:07 UTC", "RemoteUrl": "https://github.com/cran/mob", "RemoteRef": "HEAD", "RemoteSha": "1e5cb564adeeb6643fe23dd75057a3d551f45f40", "_user": "statcompute", "_type": "src", "_file": "mob_0.4.2.tar.gz", "_fileid": "https://r2.ropensci.org/4bd06b6eeb73643bae76d22ee54caee2d861e7eba243e288d4c64bbe897a02f7", "_filesize": 267656, "_sha256": "4bd06b6eeb73643bae76d22ee54caee2d861e7eba243e288d4c64bbe897a02f7", "_expires": "2027-01-16T10:57:36.000Z", "_created": "2026-10-08T10:01:17.000Z", "_published": "2026-10-08T10:57:38.547Z", "_buildurl": "https://github.com/r-universe/statcompute/actions/runs/37760322862", "_status": "success", "_host": "GitHub-Actions", "_jobs": [ { "job": 113256138584, "time": 103, "config": "linux-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "11542301501" }, { "job": 113256138800, "time": 105, "config": "linux-release-x86_64", "r": "4.6.1", "check": "OK", "artifact": "11542530982" }, { "job": 113256138751, "time": 120, "config": "macos-oldrel-arm64", "r": "4.5.3", "check": "OK", "artifact": "11543769481" }, { "job": 113256138853, "time": 106, "config": "macos-release-arm64", "r": "4.6.1", "check": "OK", "artifact": "11544638221" }, { "job": 113255017892, "time": 167, "config": "source", "r": "4.6.1", "check": "OK", "artifact": "11541843001" }, { "job": 113256138645, "time": 76, "config": "wasm-release", "r": "4.6.0", "check": "OK", "artifact": "11542341393" }, { "job": 113256138730, "time": 79, "config": "windows-devel-x86_64", "r": "4.7.0", 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"_contributors": [ { "user": "statcompute", "count": 7, "uuid": 4590938 } ], "_userbio": { "uuid": 4590938, "type": "user", "name": "WenSui Liu", "followers": 48 }, "_downloads": { "count": 321, "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/mob" }, "_mentions": 5, "_devurl": "https://github.com/statcompute/mob", "_searchresults": 59, "_rbuild": "4.6.1", "_assets": [ "extra/citation.cff", "extra/citation.html", "extra/citation.json", "extra/citation.txt", "extra/contents.json", "extra/manual.pdf", "extra/mob.html" ], "_realowner": "statcompute", "_cranurl": false, "_releases": [ { "version": "0.1.0", "date": "2020-02-29" }, { "version": "0.2.0", "date": "2020-07-05" }, { "version": "0.2.1", "date": "2020-07-06" }, { "version": "0.3", "date": "2020-11-02" }, { "version": "0.4", "date": "2021-02-17" }, { "version": "0.4.1", "date": "2021-04-05" }, { "version": "0.4.2", "date": "2021-07-31" } ], "_exports": [ "arb_bin", "bad_bin", "batch_bin", "batch_woe", "cal_woe", "gbm_bin", "iso_bin", "kmn_bin", "pool_bin", "qcut", "qtl_bin", "rng_bin" ], "_datasets": [ { "name": "hmeq", "title": "Credit attributes of 5,960 home equity loans", "object": "hmeq", "class": [ "data.frame" ], "fields": [ "BAD", "LOAN", "MORTDUE", "VALUE", "REASON", "JOB", "YOJ", "DEROG", "DELINQ", "CLAGE", "NINQ", "CLNO", "DEBTINC" ], "rows": 5960, "table": true, "tojson": true } ], "_help": [ { "page": "arb_bin", "title": "Monotonic binning based on decision tree model", "topics": [ "arb_bin" ] }, { "page": "bad_bin", "title": "Monotonic binning by quantile with cases Y = 1", "topics": [ "bad_bin" ] }, { "page": "batch_bin", "title": "Apply monotonic binning to all vectors in dataframe", "topics": [ "batch_bin" ] }, { "page": "batch_woe", "title": "Apply WoE transformations to vectors in dataframe", "topics": [ "batch_woe" ] }, { "page": "cal_woe", "title": "Perform WoE transformation of a numeric variable", "topics": [ "cal_woe" ] }, { "page": "gbm_bin", "title": "Monotonic binning based on generalized boosted model", "topics": [ "gbm_bin" ] }, { "page": "hmeq", "title": "Credit attributes of 5,960 home equity loans", "topics": [ "hmeq" ] }, { "page": "iso_bin", "title": "Monotonic binning based on isotonic regression", "topics": [ "iso_bin" ] }, { "page": "kmn_bin", "title": "Monotonic binning based on k-means clustering", "topics": [ "kmn_bin" ] }, { "page": "pool_bin", "title": "Monotonic binning for the pool data", "topics": [ "pool_bin" ] }, { "page": "qcut", "title": "Discretizing a numeric vector", "topics": [ "qcut" ] }, { "page": "qtl_bin", "title": "Monotonic binning by quantile", "topics": [ "qtl_bin" ] }, { "page": "rng_bin", "title": "Monotonic binning by quantile based on value range", "topics": [ "rng_bin" ] } ], "_rundeps": [ "data.table", "digest", "gbm", "lattice", "Matrix", "Rborist", "Rcpp", "survival" ], "_score": 2.469822015978163, "_indexed": true, "_nocasepkg": "mob", "_universes": [ "statcompute" ], "_binaries": [ { "r": "4.7.0", 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