{ "_id": "6ad32c562c5c76d3dd0c9c60", "Package": "accuracylevel", "Title": "Robust Accuracy-Level Metrics for Predictive Model Evaluation", "Version": "0.1.0", "Authors@R": "c(\nperson(\"Achmad Syahrul\", \"Choir\", email = \"madsyair@stis.ac.id\",\nrole = c(\"cre\", \"aut\")),\nperson(\"Mety\", \"Agustini\", email = \"mety.assahid@bps.go.id\",\nrole = \"aut\"),\nperson(\"Kartika\", \"Fithriasari\", email = \"kartika_f@statistika.its.ac.id\",\nrole = \"aut\"),\nperson(\"Dedy Dwi\", \"Prastyo\", email = \"dedy-dp@statistika.its.ac.id\",\nrole = \"aut\"))", "Author": "Achmad Syahrul Choir [cre, aut], Mety Agustini [aut], Kartika\nFithriasari [aut], Dedy Dwi Prastyo [aut]", "Maintainer": "Achmad Syahrul Choir ", "Description": "Implements novel accuracy-level metrics for evaluating\ncontinuous data prediction models. Four metrics are provided:\nCounted Squared Error (CSE), Counted Absolute Error (CAE),\nCounted Absolute Percentage Error (CAPE), and Symmetric Counted\nAbsolute Percentage Error (SCAPE). These metrics offer robust,\nconsistent, and interpretable evaluation on a 0-100% scale,\naddressing limitations of conventional metrics like RMSE, MAE,\nand MAPE. The package integrates with 'caret', 'tidymodels',\nand common forecasting frameworks. Based on Agustini,\nFithriasari, and Prastyo (2026)\n.", "License": "GPL-3", "Encoding": "UTF-8", "URL": "https://github.com/madsyair/accuracylevel", "BugReports": "https://github.com/madsyair/accuracylevel/issues", "Config/testthat/edition": "3", "Roxygen": "list(markdown = TRUE)", "VignetteBuilder": "knitr", "NeedsCompilation": "no", "Config/roxygen2/version": "8.0.0", "Repository": "https://madsyair.r-universe.dev", "Date/Publication": "2026-06-10 09:17:10 UTC", "RemoteUrl": "https://github.com/madsyair/accuracylevel", "RemoteRef": "HEAD", "RemoteSha": "0de6e07a12f84f294362f332216d2655a1b69014", "Packaged": { "Date": "2026-10-17 08:01:27 UTC", "User": "root" }, "_user": "madsyair", "_type": "src", "_file": "accuracylevel_0.1.0.tar.gz", "_fileid": "https://r2.ropensci.org/e0b9290068749dc91da2e77b49b45d93d33ed7fc1579b4909fa27c4f46cbb2f2", "_filesize": 282967, "_sha256": "e0b9290068749dc91da2e77b49b45d93d33ed7fc1579b4909fa27c4f46cbb2f2", "_expires": "2027-01-25T08:05:40.000Z", 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