{ "_id": "6a1025e7acfb0bcc41c8f043", "Package": "HNPclassifier", "Title": "Hierarchical Neyman-Pearson Classification for Ordered Classes", "Version": "0.1.0", "Authors@R": "c(person(given = \"Che\", family = \"Shen\", role = c(\"aut\", \"cre\"),\nemail = \"chshen3-c@my.cityu.edu.hk\", comment = \"Implementation and maintenance\"),\nperson(given = \"Lujia\", family = \"Yang\", role = \"aut\",\nemail = \"25480847@life.hkbu.edu.hk\", comment = \"Testing and debugging\"),\nperson(given = \"Lijia\", family = \"Wang\", role = \"aut\",\nemail = \"lijiwang@cityu.edu.hk\", comment = \"Original theory and supervision\"),\nperson(given = \"Shunan\", family = \"Yao\", role = \"aut\",\nemail = \"yaoshunan@hkbu.edu.hk\", comment = \"Supervision and debugging\"))", "Description": "The Hierarchical Neyman-Pearson (H-NP) classification\nframework extends the Neyman-Pearson classification paradigm to\nmulti-class settings where classes have a natural priority\nordering. This is particularly useful for classification in\nunbalanced dataset, for example, disease severity\nclassification, where under-classification errors\n(misclassifying patients into less severe categories) are more\nconsequential than other misclassifications. The package\nimplements H-NP umbrella algorithms that controls\nunder-classification errors under user specified control levels\nwith high probability. It supports the creation of H-NP\nclassifiers using scoring functions based on built-in\nclassification methods (including logistic regression, support\nvector machines, and random forests), as well as user-trained\nscoring functions. For theoretical details, please refer to\nLijia Wang, Y. X. Rachel Wang, Jingyi Jessica Li & Xin Tong\n(2024) .", "License": "MIT + file LICENSE", "Encoding": "UTF-8", "RoxygenNote": "7.3.2", "NeedsCompilation": "no", "Packaged": { "Date": "2026-05-13 09:13:23 UTC", "User": "root" }, "Author": "Che Shen [aut, cre] (Implementation and maintenance), Lujia\nYang [aut] (Testing and debugging), Lijia Wang [aut] (Original\ntheory and supervision), Shunan Yao [aut] (Supervision and\ndebugging)", "Maintainer": "Che Shen ", "Repository": "https://wobushics.r-universe.dev", "Date/Publication": "2026-02-08 16:40:07 UTC", "RemoteUrl": "https://github.com/cran/HNPclassifier", "RemoteRef": "HEAD", "RemoteSha": "98969310356c56b40ee3bbbd1c4cb562a3217815", "MD5sum": "4d5c91caeac0f076d666b843684cb64e", "_user": "wobushics", "_type": "src", "_file": "HNPclassifier_0.1.0.tar.gz", "_fileid": "68f80e13efffb77db918641a646a55a65af524754220f7deefa9af858fbe8c7d", "_filesize": 125996, "_sha256": "68f80e13efffb77db918641a646a55a65af524754220f7deefa9af858fbe8c7d", "_created": "2026-05-13T09:13:23.000Z", "_published": "2026-05-22T09:46:15.374Z", "_distro": "noble", "_jobs": [ { "job": 77355491885, "time": 111, "config": "linux-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "6966121626" }, { "job": 77355492080, "time": 107, "config": "linux-release-x86_64", "r": "4.6.0", "check": "OK", "artifact": "6966122854" }, { "job": 77355492064, "time": 176, "config": "macos-oldrel-arm64", "r": "4.5.3", "check": "OK", "artifact": "6966136606" }, { "job": 77355491940, "time": 158, "config": "macos-release-arm64", "r": "4.6.0", "check": "OK", "artifact": "6966130032" }, { "job": 77355491323, "time": 162, "config": "source", "r": "4.6.0", "check": "OK", "artifact": "6966079063" }, { "job": 77355491369, "time": 88, "config": "wasm-release", "r": "4.6.0", "check": "OK", "artifact": "7157589835" }, { "job": 77355491930, "time": 84, "config": "windows-devel", "r": "4.7.0", "check": "OK", "artifact": "6966111393" }, { "job": 77355492192, "time": 88, "config": "windows-oldrel", "r": "4.5.3", "check": "OK", "artifact": "6966113135" }, { "job": 77355491813, "time": 79, "config": "windows-release", "r": "4.6.0", "check": "OK", "artifact": "6966109526" } ], "_buildurl": "https://github.com/r-universe/wobushics/actions/runs/25789655258", "_status": "success", "_host": "GitHub-Actions", "_upstream": "https://github.com/cran/HNPclassifier", "_commit": { "id": "98969310356c56b40ee3bbbd1c4cb562a3217815", "author": "Che Shen ", "committer": "cran-robot ", "message": "version 0.1.0\n", "time": 1770568807 }, "_maintainer": { "name": "Che Shen", "email": "chshen3-c@my.cityu.edu.hk", "login": "wobushics", "uuid": 180137765 }, "_registered": true, "_dependencies": [ { "package": "dplyr", "role": "Imports" }, { "package": "e1071", "role": "Imports" }, { "package": "nnet", "role": "Imports" }, { "package": "randomForest", "role": "Imports" } ], "_owner": "cran", "_selfowned": true, "_usedby": 0, "_updates": [ { "week": "2026-06", "n": 1 } ], "_tags": [ { "name": "0.1.0", "date": "2026-02-08" } ], "_stars": 0, "_contributors": [ { "user": "wobushics", "count": 1, "uuid": 180137765 } ], "_userbio": { "uuid": 180137765, "type": "user", "name": "wobushiCS" }, "_downloads": { "count": 160, "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/HNPclassifier" }, "_searchresults": 0, "_rbuild": "4.6.0", "_assets": [ "extra/citation.cff", "extra/citation.html", "extra/citation.json", "extra/citation.txt", "extra/contents.json", "extra/HNPclassifier.html", "manual.pdf" ], "_realowner": "wobushics", "_cranurl": false, "_releases": [ { "version": "0.1.0", "date": "2026-02-08" } ], "_exports": [ "base_function", "hnp_box_plot", "hnp_delta_search", "hnp_map_classes", "hnp_summary", "hnp_umbrella", "hnp_umbrella_flex", "hnp_upper_bound", "probability_to_score_1", "probability_to_score_2" ], "_help": [ { "page": "base_function", "title": "Base Classifier Training function Train a base multi-class model (RF / SVM / Multinomial Logistic)", "topics": [ "base_function" ] }, { "page": "hnp_box_plot", "title": "HNP Box Plot Experiment", "topics": [ "hnp_box_plot" ] }, { "page": "hnp_delta_search", "title": "Delta search", "topics": [ "hnp_delta_search" ] }, { "page": "hnp_map_classes", "title": "Classes Mapping function for HNP Algorithm Map class labels to canonical levels \"1\", \"2\", \"3\"", "topics": [ "hnp_map_classes" ] }, { "page": "hnp_summary", "title": "hnp_summary Summarize a ternary classifier's performance", "topics": [ "hnp_summary" ] }, { "page": "hnp_umbrella", "title": "HNP Umbrella Algorithm", "topics": [ "hnp_umbrella" ] }, { "page": "hnp_umbrella_flex", "title": "HNP Umbrella (flex): use custom score functions and pre-split data", "topics": [ "hnp_umbrella_flex" ] }, { "page": "hnp_upper_bound", "title": "Upper Bound of the ith Threshold (Optimal ith Threshold)", "topics": [ "hnp_upper_bound" ] }, { "page": "probability_to_score_1", "title": "T1 Calculation Create T1 scoring function from a fitted model", "topics": [ "probability_to_score_1" ] }, { "page": "probability_to_score_2", "title": "T2 Calculation Create T2 scoring function as ratio P(class 2)/P(class 3)", "topics": [ "probability_to_score_2" ] } ], "_rundeps": [ "class", "cli", "dplyr", "e1071", "generics", "glue", "lifecycle", "magrittr", "MASS", "nnet", "pillar", "pkgconfig", "proxy", "R6", "randomForest", "rlang", "tibble", "tidyselect", "utf8", "vctrs", "withr" ], "_score": 1, "_indexed": true, "_nocasepkg": "hnpclassifier", "_universes": [ "wobushics" ], "_binaries": [ { "r": "4.7.0", "os": "linux", "version": "0.1.0", "date": "2026-05-13T09:15:15.000Z", "distro": "noble", "commit": "98969310356c56b40ee3bbbd1c4cb562a3217815", "fileid": "30641d523e5813043a38d14351e476b742374068dd1f538fb10f9903ae09b6fb", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/wobushics/actions/runs/25789655258" }, { "r": "4.6.0", "os": "linux", "version": "0.1.0", "date": "2026-05-13T09:15:18.000Z", "distro": "noble", "commit": "98969310356c56b40ee3bbbd1c4cb562a3217815", "fileid": "c84c2206f34bf208db81813e7a647775941e62774647ab953d1bb79d5010fa62", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/wobushics/actions/runs/25789655258" }, { "r": "4.5.3", "os": "mac", "version": "0.1.0", "date": "2026-05-13T09:16:01.000Z", "commit": "98969310356c56b40ee3bbbd1c4cb562a3217815", "fileid": "c322cda71825d059e58924f233c97349b82a587ef9069a3dd454cf146c5c3092", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/wobushics/actions/runs/25789655258" }, { "r": "4.6.0", "os": "mac", "version": "0.1.0", "date": "2026-05-13T09:15:42.000Z", "commit": "98969310356c56b40ee3bbbd1c4cb562a3217815", "fileid": "edc6525bcdea333c176c03071a03b72d4a9ddf74dc511229578d61f47dc0950e", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/wobushics/actions/runs/25789655258" }, { "r": "4.7.0", "os": "win", "version": "0.1.0", "date": "2026-05-13T09:14:44.000Z", "commit": "98969310356c56b40ee3bbbd1c4cb562a3217815", "fileid": "17fad82eb55ca4c7ee504efcb54b71e154999b05857e2c3cfc34e2ccb813e70b", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/wobushics/actions/runs/25789655258" }, { "r": "4.5.3", "os": "win", "version": "0.1.0", "date": "2026-05-13T09:14:47.000Z", "commit": "98969310356c56b40ee3bbbd1c4cb562a3217815", "fileid": "4303faaca66cc3a0b73b1e183a7f4dcfc085a21fe9592ab846c55a21087f8d8e", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/wobushics/actions/runs/25789655258" }, { "r": "4.6.0", "os": "win", "version": "0.1.0", "date": "2026-05-13T09:14:39.000Z", "commit": "98969310356c56b40ee3bbbd1c4cb562a3217815", "fileid": "47b01372292df7eea02423bc1b91f7d4ccf77c08952f38436d636ca1d4a86e70", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/wobushics/actions/runs/25789655258" }, { "r": "4.6.0", "os": "wasm", "version": "0.1.0", "date": "2026-05-22T09:46:01.000Z", "commit": "98969310356c56b40ee3bbbd1c4cb562a3217815", "fileid": "baa399d1123a88033f6886216c6d4d9a45f7e22b0fccda6d2eb1bd07a86a1e10", "status": "success", "buildurl": "https://github.com/r-universe/wobushics/actions/runs/25789655258" } ] }