{ "_id": "6abc5f5399f7aa8c6aa4a7ed", "Package": "deriva", "Title": "Tidy Drift Detection for Monitored Machine Learning Models", "Version": "0.2.0", "Authors@R": "c(\nperson(\"João Paulo Assis\", \"Bonifácio\", , \"jpab.27@hotmail.com\",\nrole = c(\"aut\", \"cre\"),\ncomment = c(ORCID = \"0009-0009-2335-8391\")),\nperson(\"Geraldo Magela da Cruz\", \"Pereira\", , \"geraldo.pereira@ufla.br\",\nrole = \"aut\",\ncomment = c(ORCID = \"0000-0001-6280-4870\")),\nperson(\"Pedro\", \"Mambelli Fernandes\", , \"pedromambelli@gmail.com\",\nrole = \"aut\",\ncomment = c(ORCID = \"0009-0001-1695-279X\"))\n)", "Description": "Detects concept drift and data drift in streams produced\nby deployed machine learning models, using a tidy interface\nthat composes with the 'tidymodels' ecosystem. Detectors are\nspecified, fitted on a baseline period, and advanced over new\nbatches of observations, returning tibbles annotated with\nwarning and drift flags. A catalogue of 22 sequential drift\ndetectors is provided. Error-based methods include the Drift\nDetection Method (DDM) of Gama et al. (2004)\n, the Early Drift Detection\nMethod (EDDM) of Baena-Garcia et al. (2006), the Hoeffding's\ninequality based Drift Detection Methods (HDDM) of Frias-Blanco\net al. (2015) , and the\nExponentially Weighted Moving Average (EWMA) chart of Ross et\nal. (2012) .\nDistribution-based methods include Adaptive Windowing (ADWIN)\nof Bifet and Gavalda (2007) ,\nKolmogorov-Smirnov Windowing (KSWIN) of Raab et al. (2020)\n, and the Page-Hinkley test\nof Page (1954) .", "License": "MIT + file LICENSE", "URL": "https://github.com/bonijoao/deriva,\nhttps://bonijoao.github.io/deriva/", "BugReports": "https://github.com/bonijoao/deriva/issues", "Encoding": "UTF-8", "LazyData": "true", "Roxygen": "list(markdown = TRUE)", "RoxygenNote": "7.3.3", "VignetteBuilder": "knitr", "Config/testthat/edition": "3", "Repository": "https://bonijoao.r-universe.dev", "Date/Publication": "2026-09-30 00:31:32 UTC", "RemoteUrl": "https://github.com/bonijoao/deriva", "RemoteRef": "HEAD", "RemoteSha": "80a697afa3427051dc00a3d49ea4f4a8702c35ed", "NeedsCompilation": "no", "Packaged": { "Date": "2026-09-30 00:56:55 UTC", "User": "root" }, "Author": "João Paulo Assis Bonifácio [aut, cre] (ORCID:\n),\nGeraldo Magela da Cruz Pereira [aut] (ORCID:\n),\nPedro Mambelli Fernandes [aut] (ORCID:\n)", "Maintainer": "João Paulo Assis Bonifácio ", "_user": "bonijoao", "_type": "src", "_file": "deriva_0.2.0.tar.gz", "_fileid": "https://r2.ropensci.org/0dcab6a1b2bba6e78c964c776a31e3d13fd13e329bab2ff87a85334345b96e46", "_filesize": 335059, "_sha256": "0dcab6a1b2bba6e78c964c776a31e3d13fd13e329bab2ff87a85334345b96e46", "_expires": "2027-01-08T01:01:01.000Z", "_created": "2026-09-30T00:56:55.000Z", "_published": "2026-09-30T01:01:07.268Z", "_jobs": [ { "job": 109690455396, "time": 179, "config": "linux-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "11070717747" }, { "job": 109690455410, "time": 164, "config": "linux-release-x86_64", "r": "4.6.1", "check": "OK", "artifact": "11070777719" }, { "job": 109690455541, "time": 114, "config": "macos-oldrel-arm64", "r": "4.5.3", "check": "OK", "artifact": "11071057261" }, { "job": 109690455526, "time": 121, "config": "macos-release-arm64", "r": "4.6.1", "check": "OK", "artifact": "11070772688" }, { "job": 109689383071, "time": 260, "config": "source", "r": "4.6.1", "check": "OK", "artifact": "11071337576" }, { "job": 109690455405, "time": 111, "config": 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"jpab.27@hotmail.com", "login": "bonijoao", "description": "Physicist | MSc & BSc in Statistics | R package developer | Time Series & Machine Learning", "uuid": 87396526, "orcid": "0009-0009-2335-8391" }, "_distro": "resolute", "_registered": true, "_dependencies": [ { "package": "R", "version": ">= 4.1", "role": "Depends" }, { "package": "cli", "role": "Imports" }, { "package": "generics", "role": "Imports" }, { "package": "rlang", "role": "Imports" }, { "package": "stats", "role": "Imports" }, { "package": "tibble", "role": "Imports" }, { "package": "utils", "role": "Imports" }, { "package": "vctrs", "role": "Imports" }, { "package": "withr", "role": "Imports" }, { "package": "ggplot2", "role": "Suggests" }, { "package": "knitr", "role": "Suggests" }, { "package": "rmarkdown", "role": "Suggests" }, { "package": "testthat", "version": ">= 3.0.0", "role": "Suggests" } ], "_owner": "bonijoao", "_selfowned": true, "_usedby": 0, "_updates": [ { "week": "2026-24", "n": 31 }, { "week": 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"title": "Build a drift signal from model predictions", "topics": [ "add_prediction_error" ] }, { "page": "advance", "title": "Advance a fitted drift detector over a new batch", "topics": [ "advance", "advance.drift_detector_fit" ] }, { "page": "augment.drift_detector_fit", "title": "Annotated observations from a fitted drift detector", "topics": [ "augment.drift_detector_fit" ] }, { "page": "autoplot.drift_detector_fit", "title": "Plot the monitored signal with drift markings", "topics": [ "autoplot.drift_detector_fit" ] }, { "page": "credit_monitoring", "title": "Simulated credit monitoring stream", "topics": [ "credit_monitoring" ] }, { "page": "detect_drift", "title": "Detect drift in a signal column (one-shot shortcut)", "topics": [ "detect_drift" ] }, { "page": "drift_detector", "title": "Specify a drift detector", "topics": [ "drift_detector" ] }, { "page": "fit.drift_detector", "title": "Fit a drift detector on a baseline period", "topics": [ "fit.drift_detector" ] }, { "page": "glance.drift_detector_fit", "title": "One-row summary of a fitted detector", "topics": [ "glance.drift_detector_fit" ] }, { "page": "sensor_monitoring", "title": "Simulated sensor monitoring stream", "topics": [ "sensor_monitoring" ] }, { "page": "sim_dist_stream", "title": "Simulate a continuous stream with a known distribution-shift point", "topics": [ "sim_dist_stream" ] }, { "page": "sim_drift_stream", "title": "Simulate a binary error stream with a known drift point", "topics": [ "sim_drift_stream" ] }, { "page": "tidy.drift_detector_fit", "title": "Drift points of a fitted detector", "topics": [ "tidy.drift_detector_fit" ] } ], "_pkglogo": "https://github.com/bonijoao/deriva/raw/HEAD/man/figures/logo.png", "_readme": "https://github.com/bonijoao/deriva/raw/HEAD/README.md", "_rundeps": [ "cli", "generics", "glue", "lifecycle", "magrittr", "pillar", "pkgconfig", "rlang", "tibble", "utf8", "vctrs", "withr" ], "_vignettes": [ { "source": "distribution-detectors.Rmd", "filename": 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