{ "_id": "6a282340a476d7de6d3c9815", "Package": "SLmetrics", "Title": "Machine Learning Performance Evaluation on Steroids", "Version": "0.3-4", "Authors@R": "c(\nperson(\ngiven = \"Serkan\",\nfamily = \"Korkmaz\",\nemail = \"serkor1@duck.com\",\nrole = c(\"cre\", \"aut\", \"cph\"),\ncomment = c(ORCID = \"0000-0002-5052-0982\")\n)\n)", "Description": "Performance evaluation metrics for supervised and\nunsupervised machine learning, statistical learning and\nartificial intelligence applications. Core computations are\nimplemented in 'C++' for scalability and efficiency.", "SystemRequirements": "C++17", "License": "GPL (>= 3)", "Encoding": "UTF-8", "Roxygen": "list(markdown = TRUE)", "RoxygenNote": "7.3.2", "Config/testthat/edition": "3", "URL": "https://slmetrics-docs.gitbook.io/v1,\nhttps://github.com/serkor1/SLmetrics", "BugReports": "https://github.com/serkor1/SLmetrics/issues", "LazyData": "true", "VignetteBuilder": "knitr", "Repository": "https://fastverse.r-universe.dev", "Date/Publication": "2025-06-21 19:57:45 UTC", "RemoteUrl": "https://github.com/serkor1/SLmetrics", "RemoteRef": "HEAD", "RemoteSha": "f15c4b758a0b4a8160ab0eed3e3d2b43d2d37b16", "NeedsCompilation": "yes", "Packaged": { "Date": "2026-06-09 14:03:59 UTC", "User": "root" }, "Author": "Serkan Korkmaz [cre, aut, cph] (ORCID:\n)", "Maintainer": "Serkan Korkmaz ", "MD5sum": "0103ebcb5de6fddef52a15ae0317537f", "_user": "fastverse", "_type": "src", "_file": "SLmetrics_0.3-4.tar.gz", "_fileid": "63e055ade0dd6621d89ac82bd3b3bf62335d6ddc67cc03cd41ffc99ebc7dc9c3", "_filesize": 2212284, "_sha256": "63e055ade0dd6621d89ac82bd3b3bf62335d6ddc67cc03cd41ffc99ebc7dc9c3", "_created": "2026-06-09T14:03:59.000Z", "_published": "2026-06-09T14:29:20.711Z", "_distro": "noble", "_jobs": [ { "job": 80343274374, "time": 408, "config": "linux-devel-arm64", "r": "4.7.0", "check": "OK", "artifact": "7510364814" }, { "job": 80343274454, "time": 431, "config": "linux-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "7510372844" }, { "job": 80343274383, "time": 405, "config": "linux-release-arm64", "r": "4.6.0", "check": "OK", "artifact": "7510362890" }, { "job": 80343274587, "time": 418, "config": "linux-release-x86_64", "r": "4.6.0", "check": "OK", "artifact": "7510367640" }, { "job": 80343274620, "time": 381, "config": "macos-oldrel-arm64", "r": "4.5.3", "check": "OK", "artifact": "7510559208" }, { "job": 80343274429, "time": 713, "config": "macos-oldrel-x86_64", "r": "4.5.3", "check": "OK", "artifact": "7510719050" }, { "job": 80343274410, "time": 277, "config": "macos-release-arm64", "r": "4.6.0", "check": "OK", "artifact": "7510504082" }, { "job": 80343274403, "time": 724, "config": "macos-release-x86_64", "r": "4.6.0", "check": "OK", "artifact": "7510727343" }, { "job": 80340793626, "time": 657, "config": "source", "r": "4.6.0", "check": "OK", "artifact": "7510175736" }, { "job": 80343274666, "time": 312, "config": "wasm-release", "r": "4.6.0", "check": "OK", "artifact": "7510320744" }, { "job": 80343274445, "time": 669, "config": "windows-devel", "r": "4.7.0", "check": "WARNING", "artifact": "7510480572" }, { "job": 80343274523, "time": 578, "config": "windows-oldrel", "r": "4.5.3", "check": "WARNING", "artifact": "7510439544" }, { "job": 80343274395, "time": 661, "config": "windows-release", "r": "4.6.0", "check": "WARNING", "artifact": "7510477149" } ], "_buildurl": "https://github.com/r-universe/fastverse/actions/runs/27211276509", "_status": "success", "_host": "GitHub-Actions", "_upstream": "https://github.com/serkor1/SLmetrics", "_commit": { "id": "f15c4b758a0b4a8160ab0eed3e3d2b43d2d37b16", "author": "serkor1 <77464572+serkor1@users.noreply.github.com>", "committer": "serkor1 <77464572+serkor1@users.noreply.github.com>", "message": ":hammer: Deleted documentation templates\n\n* The _documentation files are working as expected;\n But they are are failing on R-devel checks on CRAN machines.\n", "time": 1750535865 }, "_maintainer": { "name": "Serkan Korkmaz", "email": "serkor1@duck.com", "orcid": "0000-0002-5052-0982" }, "_registered": true, "_dependencies": [ { "package": "R", "version": ">= 4.0.0", "role": "Depends" }, { "package": "Rcpp", "role": "LinkingTo" }, { "package": "RcppArmadillo", "role": "LinkingTo" }, { "package": "grDevices", "role": "Imports" }, { "package": "lattice", "role": "Imports" }, { "package": "Rcpp", "role": "Imports" }, { "package": "knitr", "role": "Suggests" }, { "package": "reticulate", "role": "Suggests" }, { "package": "rmarkdown", "role": "Suggests" }, { "package": "testthat", "version": ">= 3.0.0", "role": "Suggests" } ], "_owner": "serkor1", "_selfowned": false, "_usedby": 0, "_updates": [ { "week": "2025-25", "n": 3 } ], "_tags": [], "_topics": [ "armadillo", "armadillo-library", "artificial-intelligence", "cpp", "data-analysis", "data-science", "eigen3", "machine-learning", "performance-metrics", "rcpp", "rcpparmadillo", "rcppeigen", "statistics", "supervised-learning", "openblas", "cpp", "openmp" ], "_stars": 27, "_contributors": [ { "user": "serkor1", "count": 169, "uuid": 77464572 } ], "_userbio": { "uuid": 105517888, "type": "organization", "name": "fastverse", "description": "An Extensible Suite of High-Performance and Low-Dependency Packages for Statistical Computing and Data Manipulation in R" }, "_downloads": { "count": 15, "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/SLmetrics" }, "_devurl": "https://github.com/serkor1/slmetrics", "_searchresults": 7, "_rbuild": "4.6.0", "_assets": [ "extra/citation.cff", "extra/citation.html", "extra/citation.json", "extra/citation.txt", "extra/contents.json", "extra/NEWS.html", "extra/NEWS.txt", "extra/readme.html", "extra/readme.md", "extra/SLmetrics.html", "manual.pdf" ], "_cranurl": false, "_releases": [ { "version": "0.3-3", "date": "2025-03-22" }, { "version": "0.3-4", "date": "2025-06-21" } ], "_exports": [ "accuracy", "auc.pr.curve", "auc.roc.curve", "auc.xy", "baccuracy", "brier.score", "ccc", "ckappa", "cmatrix", "cross.entropy", "csi", "deviance.gamma", "deviance.poisson", "deviance.tweedie", "dor", "fallout", "fbeta", "fdr", "fer", "fmi", "fpr", "gmse", "hammingloss", "huberloss", "jaccard", "logloss", "maape", "mae", "mape", "mcc", "mpe", "mse", "nlr", "npv", "openmp.off", "openmp.on", "openmp.threads", "phi", "pinball", "plr", "ppv", "pr.curve", "precision", "preorder", "presort", "rae", "recall", "relative.entropy", "rmse", "rmsle", "roc.curve", "rrmse", "rrse", "rsq", "selectivity", "sensitivity", "shannon.entropy", "smape", "specificity", "tnr", "tpr", "tscore", "weighted.accuracy", "weighted.auc.pr.curve", "weighted.auc.roc.curve", "weighted.baccuracy", "weighted.brier.score", "weighted.ccc", "weighted.ckappa", "weighted.cmatrix", "weighted.csi", "weighted.deviance.gamma", "weighted.deviance.poisson", "weighted.deviance.tweedie", "weighted.dor", "weighted.fallout", "weighted.fbeta", "weighted.fdr", "weighted.fer", "weighted.fmi", "weighted.fpr", "weighted.gmse", "weighted.hammingloss", "weighted.huberloss", "weighted.jaccard", "weighted.logloss", "weighted.maape", "weighted.mae", "weighted.mape", "weighted.mcc", "weighted.mpe", "weighted.mse", "weighted.nlr", "weighted.npv", "weighted.phi", "weighted.pinball", "weighted.plr", "weighted.ppv", "weighted.pr.curve", "weighted.precision", "weighted.rae", "weighted.recall", "weighted.rmse", "weighted.rmsle", "weighted.roc.curve", "weighted.rrmse", "weighted.rrse", "weighted.rsq", "weighted.selectivity", "weighted.sensitivity", "weighted.smape", "weighted.specificity", "weighted.tnr", "weighted.tpr", "weighted.tscore", "weighted.zerooneloss", "zerooneloss" ], "_datasets": [ { "name": "banknote", "title": "Banknote authentication dataset", "object": "banknote", "class": [ "list" ], "fields": [], "table": false, "tojson": true }, { "name": "obesity", "title": "Obesity levels dataset", "object": "obesity", "class": [ "list" ], "fields": [], "table": false, "tojson": true }, { "name": "wine.quality", "title": "Wine quality dataset", "object": "wine.quality", "class": [ "list" ], "fields": [], "table": false, "tojson": true } ], "_help": [ { "page": "classification_accuracy", "title": "Accuracy", "concept": [ "Classification", "Machine learning", "Performance evaluation", "Statistical learning", "Supervised Learning" ], "topics": [ "accuracy", "weighted.accuracy" ] }, { "page": "classification_accuracy.cmatrix", "title": "Accuracy", "concept": [ "Machine learning performance evaluation" ], "topics": [ "accuracy.cmatrix" ] }, { "page": "classification_accuracy.factor", "title": "Accuracy", "concept": [ "Machine learning performance evaluation" ], "topics": [ "accuracy.factor" ] }, { "page": "classification_auc.pr.curve", "title": "Area under the Precision Recall Curve", "concept": [ "Classification", "Machine learning", "Performance evaluation", "Statistical learning", "Supervised Learning" ], "topics": [ "auc.pr.curve", "weighted.auc.pr.curve" ] }, { "page": "classification_auc.pr.curve.factor", "title": "Area under the Precision Recall Curve", "concept": [ "Machine learning performance evaluation" ], "topics": [ "auc.pr.curve.factor" ] }, { "page": "classification_auc.roc.curve", "title": "Area under the Receiver Operator Characteristics Curve", "concept": [ "Classification", "Machine learning", "Performance evaluation", "Statistical learning", "Supervised Learning" ], "topics": [ "auc.roc.curve", "weighted.auc.roc.curve" ] }, { "page": "classification_auc.roc.curve.factor", "title": "Area under the Receiver Operator Characteristics Curve", "concept": [ "Machine learning performance evaluation" ], "topics": [ "auc.roc.curve.factor" ] }, { "page": "tools_auc.xy", "title": "Area under the curve", "concept": [ "Tools" ], "topics": [ "auc.xy" ] }, { "page": "tools_auc.xy.numeric", "title": "Area under the curve", "topics": [ "auc.xy.numeric" ] }, { "page": "classification_baccuracy", "title": "Balanced Accuracy", "concept": [ "Classification", "Machine learning", "Performance evaluation", "Statistical learning", "Supervised Learning" ], "topics": [ "baccuracy", "weighted.baccuracy" ] }, { "page": "classification_baccuracy.cmatrix", "title": "Balanced Accuracy", "concept": [ "Machine learning performance evaluation" ], "topics": [ "baccuracy.cmatrix" ] }, { "page": "classification_baccuracy.factor", "title": "Balanced Accuracy", "concept": [ "Machine learning performance evaluation" ], "topics": [ "baccuracy.factor" ] }, { "page": "data_banknote", "title": "Banknote authentication dataset", "topics": [ "banknote" ] }, { "page": "classification_brier.score", "title": "Brier Score", "concept": [ "Classification", "Machine learning", "Performance evaluation", "Proper scoring rules", "Statistical learning", "Supervised Learning" ], "topics": [ "brier.score", "weighted.brier.score" ] }, { "page": "classification_brier.score.matrix", "title": "Brier Score", "concept": [ "Machine learning performance evaluation" ], "topics": [ "brier.score.matrix" ] }, { "page": "regression_ccc", "title": "Concordance Correlation Coefficient", "concept": [ "Machine learning", "Performance evaluation", "Regression", "Statistical learning", "Supervised Learning" ], "topics": [ "ccc", "weighted.ccc" ] }, { "page": "regression_ccc.numeric", "title": "Concordance Correlation Coefficient", "concept": [ "Machine learning performance evaluation" ], "topics": [ "ccc.numeric" ] }, { "page": "classification_ckappa", "title": "Cohen's kappa-Statistic", "concept": [ "Classification", "Machine learning", "Performance evaluation", "Statistical learning", "Supervised Learning" ], "topics": [ "ckappa", "weighted.ckappa" ] }, { "page": "classification_ckappa.cmatrix", "title": "Cohen's kappa-Statistic", "concept": [ "Machine learning performance evaluation" ], "topics": [ "ckappa.cmatrix" ] }, { "page": "classification_ckappa.factor", "title": "Cohen's kappa-Statistic", "concept": [ "Machine learning performance evaluation" ], "topics": [ "ckappa.factor" ] }, { "page": "classification_cmatrix", "title": "Confusion Matrix", "concept": [ "Classification", "Machine learning", "Performance evaluation", "Statistical learning", "Supervised Learning" ], "topics": [ "cmatrix", "weighted.cmatrix" ] }, { "page": "classification_cmatrix.factor", "title": "Confusion Matrix", "concept": [ "Machine learning performance evaluation" ], "topics": [ "cmatrix.factor" ] }, { "page": "classification_cross.entropy", "title": "Cross Entropy", "concept": [ "Classification", "Entropy", "Machine learning", "Performance evaluation", "Statistical learning", "Supervised Learning" ], "topics": [ "cross.entropy" ] }, { "page": "classification_cross.entropy.matrix", "title": "Cross Entropy", "concept": [ "Machine learning performance evaluation" ], "topics": [ "cross.entropy.matrix" ] }, { "page": "regression_deviance.gamma", "title": "Gamma Deviance", "concept": [ "Machine learning", "Performance evaluation", "Regression", "Statistical learning", "Supervised Learning" ], "topics": [ "deviance.gamma", "weighted.deviance.gamma" ] }, { "page": "regression_deviance.gamma.numeric", "title": "Gamma Deviance", "concept": [ "Machine learning performance evaluation" ], "topics": [ "deviance.gamma.numeric" ] }, { "page": "regression_deviance.poisson", "title": "Poisson Deviance", "concept": [ "Machine learning", "Performance evaluation", "Regression", "Statistical learning", "Supervised Learning" ], "topics": [ "deviance.poisson", "weighted.deviance.poisson" ] }, { "page": "regression_deviance.poisson.numeric", "title": "Poisson Deviance", "concept": [ "Machine learning performance evaluation" ], "topics": [ "deviance.poisson.numeric" ] }, { "page": "regression_deviance.tweedie", "title": "Tweedie Deviance", "concept": [ "Machine learning", "Performance evaluation", "Regression", "Statistical learning", "Supervised Learning" ], "topics": [ "deviance.tweedie", "weighted.deviance.tweedie" ] }, { "page": "regression_deviance.tweedie.numeric", "title": "Tweedie Deviance", "concept": [ "Machine learning performance evaluation" ], "topics": [ "deviance.tweedie.numeric" ] }, { "page": "classification_dor", "title": "Diagnostic Odds Ratio", "concept": [ "Classification", "Machine learning", "Performance evaluation", "Statistical learning", "Supervised Learning" ], "topics": [ "dor" ] }, { "page": "classification_dor.cmatrix", "title": "Diagnostic Odds Ratio", "concept": [ "Machine learning performance evaluation" ], "topics": [ "dor.cmatrix" ] }, { "page": "classification_dor.factor", "title": "Diagnostic Odds Ratio", "concept": [ "Machine learning performance evaluation" ], "topics": [ "dor.factor" ] }, { "page": "classification_fbeta", "title": "f_{beta}", "concept": [ "Classification", "Machine learning", "Performance evaluation", "Statistical learning", "Supervised Learning" ], "topics": [ "fbeta", "weighted.fbeta" ] }, { "page": "classification_fbeta.cmatrix", "title": "f_{beta}", "concept": [ "Machine learning performance evaluation" ], "topics": [ "fbeta.cmatrix" ] }, { "page": "classification_fbeta.factor", "title": "f_{beta}", "concept": [ "Machine learning performance evaluation" ], "topics": [ "fbeta.factor" ] }, { "page": "classification_fdr", "title": "False Discovery Rate", "concept": [ "Classification", "Machine learning", "Performance evaluation", "Statistical learning", "Supervised Learning" ], "topics": [ "fdr", "weighted.fdr" ] }, { "page": "classification_fdr.cmatrix", "title": "False Discovery Rate", "concept": [ "Machine learning performance evaluation" ], "topics": [ "fdr.cmatrix" ] }, { "page": "classification_fdr.factor", "title": "False Discovery Rate", "concept": [ "Machine learning performance evaluation" ], "topics": [ "fdr.factor" ] }, { "page": "classification_fer", "title": "False Omission Rate", "concept": [ "Classification", "Machine learning", "Performance evaluation", "Statistical learning", "Supervised Learning" ], "topics": [ "fer", "weighted.fer" ] }, { "page": "classification_fer.cmatrix", "title": "False Omission Rate", "concept": [ "Machine learning performance evaluation" ], "topics": [ "fer.cmatrix" ] }, { "page": "classification_fer.factor", "title": "False Omission Rate", "concept": [ "Machine learning performance evaluation" ], "topics": [ "fer.factor" ] }, { "page": "classification_fmi", "title": "Fowlkes Mallows Index", "concept": [ "Classification", "Machine learning", "Performance evaluation", "Statistical learning", "Supervised Learning" ], "topics": [ "fmi", "weighted.fmi" ] }, { "page": "classification_fmi.cmatrix", "title": "Fowlkes Mallows Index", "concept": [ "Machine learning performance evaluation" ], "topics": [ "fmi.cmatrix" ] }, { "page": "classification_fmi.factor", "title": "Fowlkes Mallows Index", "concept": [ "Machine learning performance evaluation" ], "topics": [ "fmi.factor" ] }, { "page": "classification_fpr", "title": "False Positive Rate", "concept": [ "Classification", "Machine learning", "Performance evaluation", "Statistical learning", "Supervised Learning" ], "topics": [ "fallout", "fpr", "weighted.fallout", "weighted.fpr" ] }, { "page": "classification_fpr.cmatrix", "title": "False Positive Rate", "concept": [ "Machine learning performance evaluation" ], "topics": [ "fpr.cmatrix" ] }, { "page": "classification_fpr.factor", "title": "False Positive Rate", "concept": [ "Machine learning performance evaluation" ], "topics": [ "fpr.factor" ] }, { "page": "regression_gmse", "title": "Geometric Mean Squared Error", "concept": [ "Machine learning", "Performance evaluation", "Regression", "Statistical learning", "Supervised Learning" ], "topics": [ "gmse", "weighted.gmse" ] }, { "page": "regression_gmse.numeric", "title": "Geometric Mean Squared Error", "concept": [ "Machine learning performance evaluation" ], "topics": [ "gmse.numeric" ] }, { "page": "classification_hammingloss", "title": "Hamming Loss", "concept": [ "Classification", "Machine learning", "Performance evaluation", "Statistical learning", "Supervised Learning" ], "topics": [ "hammingloss", "weighted.hammingloss" ] }, { "page": "classification_hammingloss.cmatrix", "title": "Hamming Loss", "concept": [ "Machine learning performance evaluation" ], "topics": [ "hammingloss.cmatrix" ] }, { "page": "classification_hammingloss.factor", "title": "Hamming Loss", "concept": [ "Machine learning performance evaluation" ], "topics": [ "hammingloss.factor" ] }, { "page": "regression_huberloss", "title": "Huber Loss", "concept": [ "Machine learning", "Performance evaluation", "Regression", "Statistical learning", "Supervised Learning" ], "topics": [ "huberloss", "weighted.huberloss" ] }, { "page": "regression_huberloss.numeric", "title": "Huber Loss", "concept": [ "Machine learning performance evaluation" ], "topics": [ "huberloss.numeric" ] }, { "page": "classification_jaccard", "title": "Jaccard Index", "concept": [ "Classification", "Machine learning", "Performance evaluation", "Statistical learning", "Supervised Learning" ], "topics": [ "csi", "jaccard", "tscore", "weighted.csi", "weighted.jaccard", "weighted.tscore" ] }, { "page": "classification_jaccard.cmatrix", "title": "Jaccard Index", "concept": [ "Machine learning performance evaluation" ], "topics": [ "jaccard.cmatrix" ] }, { "page": "classification_jaccard.factor", "title": "Jaccard Index", "concept": [ "Machine learning performance evaluation" ], "topics": [ "jaccard.factor" ] }, { "page": "classification_logloss", "title": "Logarithmic Loss", "concept": [ "Classification", "Entropy", "Machine learning", "Performance evaluation", "Statistical learning", "Supervised Learning" ], "topics": [ "logloss", "weighted.logloss" ] }, { "page": "classification_logloss.factor", "title": "Logarithmic Loss", "concept": [ "Machine learning performance evaluation" ], "topics": [ "logloss.factor" ] }, { "page": "classification_logloss.integer", "title": "Logarithmic Loss", "concept": [ "Machine learning performance evaluation" ], "topics": [ "logloss.integer" ] }, { "page": "regression_maape", "title": "Mean Arctangent Absolute Percentage Error", "concept": [ "Machine learning", "Performance evaluation", "Regression", "Statistical learning", "Supervised Learning" ], "topics": [ "maape", "weighted.maape" ] }, { "page": "regression_maape.numeric", "title": "Mean Arctangent Absolute Percentage Error", "concept": [ "Machine learning performance evaluation" ], "topics": [ "maape.numeric" ] }, { "page": "regression_mae", "title": "Mean Absolute Error", "concept": [ "Machine learning", "Performance evaluation", "Regression", "Statistical learning", "Supervised Learning" ], "topics": [ "mae", "weighted.mae" ] }, { "page": "regression_mae.numeric", "title": "Mean Absolute Error", "concept": [ "Machine learning performance evaluation" ], "topics": [ "mae.numeric" ] }, { "page": "regression_mape", "title": "Mean Absolute Percentage Error", "concept": [ "Machine learning", "Performance evaluation", "Regression", "Statistical learning", "Supervised Learning" ], "topics": [ "mape", "weighted.mape" ] }, { "page": "regression_mape.numeric", "title": "Mean Absolute Percentage Error", "concept": [ "Machine learning performance evaluation" ], "topics": [ "mape.numeric" ] }, { "page": "classification_mcc", "title": "Matthews Correlation Coefficient", "concept": [ "Classification", "Machine learning", "Performance evaluation", "Statistical learning", "Supervised Learning" ], "topics": [ "mcc", "phi", "weighted.mcc", "weighted.phi" ] }, { "page": "classification_mcc.cmatrix", "title": "Matthews Correlation Coefficient", "concept": [ "Machine learning performance evaluation" ], "topics": [ "mcc.cmatrix" ] }, { "page": "classification_mcc.factor", "title": "Matthews Correlation Coefficient", "concept": [ "Machine learning performance evaluation" ], "topics": [ "mcc.factor" ] }, { "page": "regression_mpe", "title": "Mean Percentage Error", "concept": [ "Machine learning", "Performance evaluation", "Regression", "Statistical learning", "Supervised Learning" ], "topics": [ "mpe", "weighted.mpe" ] }, { "page": "regression_mpe.numeric", "title": "Mean Percentage Error", "concept": [ "Machine learning performance evaluation" ], "topics": [ "mpe.numeric" ] }, { "page": "regression_mse", "title": "Mean Squared Error", "concept": [ "Machine learning", "Performance evaluation", "Regression", "Statistical learning", "Supervised Learning" ], "topics": [ "mse", "weighted.mse" ] }, { "page": "regression_mse.numeric", "title": "Mean Squared Error", "concept": [ "Machine learning performance evaluation" ], "topics": [ "mse.numeric" ] }, { "page": "classification_nlr", "title": "Negative Likelihood Ratio", "concept": [ "Classification", "Machine learning", "Performance evaluation", "Statistical learning", "Supervised Learning" ], "topics": [ "nlr", "weighted.nlr" ] }, { "page": "classification_nlr.cmatrix", "title": "Negative Likelihood Ratio", "concept": [ "Machine learning performance evaluation" ], "topics": [ "nlr.cmatrix" ] }, { "page": "classification_nlr.factor", "title": "Negative Likelihood Ratio", "concept": [ "Machine learning performance evaluation" ], "topics": [ "nlr.factor" ] }, { "page": "classification_npv", "title": "Negative Predictive Value", "concept": [ "Classification", "Machine learning", "Performance evaluation", "Statistical learning", "Supervised Learning" ], "topics": [ "npv", "weighted.npv" ] }, { "page": "classification_npv.cmatrix", "title": "Negative Predictive Value", "concept": [ "Machine learning performance evaluation" ], "topics": [ "npv.cmatrix" ] }, { "page": "classification_npv.factor", "title": "Negative Predictive Value", "concept": [ "Machine learning performance evaluation" ], "topics": [ "npv.factor" ] }, { "page": "data_obesity", "title": "Obesity levels dataset", "topics": [ "obesity" ] }, { "page": "utils_OpenMP", "title": "Control OpenMP", "topics": [ "OpenMP", "openmp.off", "openmp.on", "openmp.threads" ] }, { "page": "regression_pinball", "title": "Pinball Loss", "concept": [ "Machine learning", "Performance evaluation", "Regression", "Statistical learning", "Supervised Learning" ], "topics": [ "pinball", "weighted.pinball" ] }, { "page": "regression_pinball.numeric", "title": "Pinball Loss", "concept": [ "Machine learning performance evaluation" ], "topics": [ "pinball.numeric" ] }, { "page": "classification_plr", "title": "Positive Likelihood Ratio", "concept": [ "Classification", "Machine learning", "Performance evaluation", "Statistical learning", "Supervised Learning" ], "topics": [ "plr", "weighted.dor", "weighted.plr" ] }, { "page": "classification_plr.cmatrix", "title": "Positive Likelihood Ratio", "concept": [ "Machine learning performance evaluation" ], "topics": [ "plr.cmatrix" ] }, { "page": "classification_plr.factor", "title": "Positive Likelihood Ratio", "concept": [ "Machine learning performance evaluation" ], "topics": [ "plr.factor" ] }, { "page": "classification_pr.curve", "title": "Precision Recall Curve", "concept": [ "Classification", "Machine learning", "Performance evaluation", "Statistical learning", "Supervised Learning" ], "topics": [ "pr.curve", "weighted.pr.curve" ] }, { "page": "classification_pr.curve.factor", "title": "Precision Recall Curve", "concept": [ "Machine learning performance evaluation" ], "topics": [ "pr.curve.factor" ] }, { "page": "classification_precision", "title": "Precision", "concept": [ "Classification", "Machine learning", "Performance evaluation", "Statistical learning", "Supervised Learning" ], "topics": [ "ppv", "precision", "weighted.ppv", "weighted.precision" ] }, { "page": "classification_precision.cmatrix", "title": "Precision", "concept": [ "Machine learning performance evaluation" ], "topics": [ "precision.cmatrix" ] }, { "page": "classification_precision.factor", "title": "Precision", "concept": [ "Machine learning performance evaluation" ], "topics": [ "precision.factor" ] }, { "page": "utils_preorder", "title": "Preorder Matrices", "concept": [ "Utilities" ], "topics": [ "preorder" ] }, { "page": "utils_preorder.matrix", "title": "Preorder Matrices", "topics": [ "preorder.matrix" ] }, { "page": "utils_presort", "title": "Presort Matrices", "concept": [ "Utilities" ], "topics": [ "presort" ] }, { "page": "utils_presort.matrix", "title": "Presort Matrices", "topics": [ "presort.matrix" ] }, { "page": "regression_rae", "title": "Relative Absolute Error", "concept": [ "Machine learning", "Performance evaluation", "Regression", "Statistical learning", "Supervised Learning" ], "topics": [ "rae", "weighted.rae" ] }, { "page": "regression_rae.numeric", "title": "Relative Absolute Error", "concept": [ "Machine learning performance evaluation" ], "topics": [ "rae.numeric" ] }, { "page": "classification_recall", "title": "Recall", "concept": [ "Classification", "Machine learning", "Performance evaluation", "Statistical learning", "Supervised Learning" ], "topics": [ "recall", "sensitivity", "tpr", "weighted.recall", "weighted.sensitivity", "weighted.tpr" ] }, { "page": "classification_recall.cmatrix", "title": "Recall", "concept": [ "Machine learning performance evaluation" ], "topics": [ "recall.cmatrix" ] }, { "page": "classification_recall.factor", "title": "Recall", "concept": [ "Machine learning performance evaluation" ], "topics": [ "recall.factor" ] }, { "page": "classification_relative.entropy", "title": "Relative Entropy", "concept": [ "Classification", "Entropy", "Machine learning", "Performance evaluation", "Statistical learning", "Supervised Learning" ], "topics": [ "relative.entropy" ] }, { "page": "classification_relative.entropy.matrix", "title": "Relative Entropy", "concept": [ "Machine learning performance evaluation" ], "topics": [ "relative.entropy.matrix" ] }, { "page": "regression_rmse", "title": "Root Mean Squared Error", "concept": [ "Machine learning", "Performance evaluation", "Regression", "Statistical learning", "Supervised Learning" ], "topics": [ "rmse", "weighted.rmse" ] }, { "page": "regression_rmse.numeric", "title": "Root Mean Squared Error", "concept": [ "Machine learning performance evaluation" ], "topics": [ "rmse.numeric" ] }, { "page": "regression_rmsle", "title": "Root Mean Squared Logarithmic Error", "concept": [ "Machine learning", "Performance evaluation", "Regression", "Statistical learning", "Supervised Learning" ], "topics": [ "rmsle", "weighted.rmsle" ] }, { "page": "regression_rmsle.numeric", "title": "Root Mean Squared Logarithmic Error", "concept": [ "Machine learning performance evaluation" ], "topics": [ "rmsle.numeric" ] }, { "page": "classification_roc.curve", "title": "Reciever Operator Characteristics", "concept": [ "Classification", "Machine learning", "Performance evaluation", "Statistical learning", "Supervised Learning" ], "topics": [ "roc.curve", "weighted.roc.curve" ] }, { "page": "classification_roc.curve.factor", "title": "Reciever Operator Characteristics", "concept": [ "Machine learning performance evaluation" ], "topics": [ "roc.curve.factor" ] }, { "page": "regression_rrmse", "title": "Relative Root Mean Squared Error", "concept": [ "Machine learning", "Performance evaluation", "Regression", "Statistical learning", "Supervised Learning" ], "topics": [ "rrmse", "weighted.rrmse" ] }, { "page": "regression_rrmse.numeric", "title": "Relative Root Mean Squared Error", "concept": [ "Machine learning performance evaluation" ], "topics": [ "rrmse.numeric" ] }, { "page": "regression_rrse", "title": "Root Relative Squared Error", "concept": [ "Machine learning", "Performance evaluation", "Regression", "Statistical learning", "Supervised Learning" ], "topics": [ "rrse", "weighted.rrse" ] }, { "page": "regression_rrse.numeric", "title": "Root Relative Squared Error", "concept": [ "Machine learning performance evaluation" ], "topics": [ "rrse.numeric" ] }, { "page": "regression_rsq", "title": "r^2", "concept": [ "Machine learning", "Performance evaluation", "Regression", "Statistical learning", "Supervised Learning" ], "topics": [ "rsq", "weighted.rsq" ] }, { "page": "regression_rsq.numeric", "title": "r^2", "concept": [ "Machine learning performance evaluation" ], "topics": [ "rsq.numeric" ] }, { "page": "classification_shannon.entropy", "title": "Shannon Entropy", "concept": [ "Classification", "Entropy", "Machine learning", "Performance evaluation", "Statistical learning", "Supervised Learning" ], "topics": [ "shannon.entropy" ] }, { "page": "classification_shannon.entropy.matrix", "title": "Shannon Entropy", "concept": [ "Machine learning performance evaluation" ], "topics": [ "shannon.entropy.matrix" ] }, { "page": "regression_smape", "title": "Symmetric Mean Absolutte Percentage Error", "concept": [ "Machine learning", "Performance evaluation", "Regression", "Statistical learning", "Supervised Learning" ], "topics": [ "smape", "weighted.smape" ] }, { "page": "regression_smape.numeric", "title": "Symmetric Mean Absolutte Percentage Error", "concept": [ "Machine learning performance evaluation" ], "topics": [ "smape.numeric" ] }, { "page": "classification_specificity", "title": "Specificity", "concept": [ "Classification", "Machine learning", "Performance evaluation", "Statistical learning", "Supervised Learning" ], "topics": [ "selectivity", "specificity", "tnr", "weighted.selectivity", "weighted.specificity", "weighted.tnr" ] }, { "page": "classification_specificity.cmatrix", "title": "Specificity", "concept": [ "Machine learning performance evaluation" ], "topics": [ "specificity.cmatrix" ] }, { "page": "classification_specificity.factor", "title": "Specificity", "concept": [ "Machine learning performance evaluation" ], "topics": [ "specificity.factor" ] }, { "page": "classification_weighted.accuracy.factor", "title": "Accuracy", "concept": [ "Machine learning performance evaluation" ], "topics": [ "weighted.accuracy.factor" ] }, { "page": "classification_weighted.auc.pr.curve.factor", "title": "Area under the Precision Recall Curve", "concept": [ "Machine learning performance evaluation" ], "topics": [ "weighted.auc.pr.curve.factor" ] }, { "page": "classification_weighted.auc.roc.curve.factor", "title": "Area under the Receiver Operator Characteristics Curve", "concept": [ "Machine learning performance evaluation" ], "topics": [ "weighted.auc.roc.curve.factor" ] }, { "page": "classification_weighted.baccuracy.factor", "title": "Balanced Accuracy", "concept": [ "Machine learning performance evaluation" ], "topics": [ "weighted.baccuracy.factor" ] }, { "page": "classification_weighted.brier.score.matrix", "title": "Brier Score", "concept": [ "Machine learning performance evaluation" ], "topics": [ "weighted.brier.score.matrix" ] }, { "page": "regression_weighted.ccc.numeric", "title": "Concordance Correlation Coefficient", "concept": [ "Machine learning performance evaluation" ], "topics": [ "weighted.ccc.numeric" ] }, { "page": "classification_weighted.ckappa.factor", "title": "Cohen's kappa-Statistic", "concept": [ "Machine learning performance evaluation" ], "topics": [ "weighted.ckappa.factor" ] }, { "page": "classification_weighted.cmatrix.factor", "title": "Confusion Matrix", "concept": [ "Machine learning performance evaluation" ], "topics": [ "weighted.cmatrix.factor" ] }, { "page": "regression_weighted.deviance.gamma.numeric", "title": "Gamma Deviance", "concept": [ "Machine learning performance evaluation" ], "topics": [ "weighted.deviance.gamma.numeric" ] }, { "page": "regression_weighted.deviance.poisson.numeric", "title": "Poisson Deviance", "concept": [ "Machine learning performance evaluation" ], "topics": [ "weighted.deviance.poisson.numeric" ] }, { "page": "regression_weighted.deviance.tweedie.numeric", "title": "Tweedie Deviance", "concept": [ "Machine learning performance evaluation" ], "topics": [ "weighted.deviance.tweedie.numeric" ] }, { "page": "classification_weighted.dor.factor", "title": "Positive Likelihood Ratio", "concept": [ "Machine learning performance evaluation" ], "topics": [ "weighted.dor.factor" ] }, { "page": "classification_weighted.fbeta.factor", "title": "f_{beta}", "concept": [ "Machine learning performance evaluation" ], "topics": [ "weighted.fbeta.factor" ] }, { "page": "classification_weighted.fdr.factor", "title": "False Discovery Rate", "concept": [ "Machine learning performance evaluation" ], "topics": [ "weighted.fdr.factor" ] }, { "page": "classification_weighted.fer.factor", "title": "False Omission Rate", "concept": [ "Machine learning performance evaluation" ], "topics": [ "weighted.fer.factor" ] }, { "page": "classification_weighted.fmi.factor", "title": "Fowlkes Mallows Index", "concept": [ "Machine learning performance evaluation" ], "topics": [ "weighted.fmi.factor" ] }, { "page": "classification_weighted.fpr.factor", "title": "False Positive Rate", "concept": [ "Machine learning performance evaluation" ], "topics": [ "weighted.fpr.factor" ] }, { "page": "regression_weighted.gmse.numeric", "title": "Geometric Mean Squared Error", "concept": [ "Machine learning performance evaluation" ], "topics": [ "weighted.gmse.numeric" ] }, { "page": "classification_weighted.hammingloss.factor", "title": "Hamming Loss", "concept": [ "Machine learning performance evaluation" ], "topics": [ "weighted.hammingloss.factor" ] }, { "page": "regression_weighted.huberloss.numeric", "title": "Huber Loss", "concept": [ "Machine learning performance evaluation" ], "topics": [ "weighted.huberloss.numeric" ] }, { "page": "classification_weighted.jaccard.factor", "title": "Jaccard Index", "concept": [ "Machine learning performance evaluation" ], "topics": [ "weighted.jaccard.factor" ] }, { "page": "classification_weighted.logloss.factor", "title": "Logarithmic Loss", "concept": [ "Machine learning performance evaluation" ], "topics": [ "weighted.logloss.factor" ] }, { "page": "classification_weighted.logloss.integer", "title": "Logarithmic Loss", "concept": [ "Machine learning performance evaluation" ], "topics": [ "weighted.logloss.integer" ] }, { "page": "regression_weighted.maape.numeric", "title": "Mean Arctangent Absolute Percentage Error", "concept": [ "Machine learning performance evaluation" ], "topics": [ "weighted.maape.numeric" ] }, { "page": "regression_weighted.mae.numeric", "title": "Mean Absolute Error", "concept": [ "Machine learning performance evaluation" ], "topics": [ "weighted.mae.numeric" ] }, { "page": "regression_weighted.mape.numeric", "title": "Mean Absolute Percentage Error", "concept": [ "Machine learning performance evaluation" ], "topics": [ "weighted.mape.numeric" ] }, { "page": "classification_weighted.mcc.factor", "title": "Matthews Correlation Coefficient", "concept": [ "Machine learning performance evaluation" ], "topics": [ "weighted.mcc.factor" ] }, { "page": "regression_weighted.mpe.numeric", "title": "Mean Percentage Error", "concept": [ "Machine learning performance evaluation" ], "topics": [ "weighted.mpe.numeric" ] }, { "page": "regression_weighted.mse.numeric", "title": "Mean Squared Error", "concept": [ "Machine learning performance evaluation" ], "topics": [ "weighted.mse.numeric" ] }, { "page": "classification_weighted.nlr.factor", "title": "Negative Likelihood Ratio", "concept": [ "Machine learning performance evaluation" ], "topics": [ "weighted.nlr.factor" ] }, { "page": "classification_weighted.npv.factor", "title": "Negative Predictive Value", "concept": [ "Machine learning performance evaluation" ], "topics": [ "weighted.npv.factor" ] }, { "page": "regression_weighted.pinball.numeric", "title": "Pinball Loss", "concept": [ "Machine learning performance evaluation" ], "topics": [ "weighted.pinball.numeric" ] }, { "page": "classification_weighted.plr.factor", "title": "Positive Likelihood Ratio", "concept": [ "Machine learning performance evaluation" ], "topics": [ "weighted.plr.factor" ] }, { "page": "classification_weighted.pr.curve.factor", "title": "Precision Recall Curve", "concept": [ "Machine learning performance evaluation" ], "topics": [ "weighted.pr.curve.factor" ] }, { "page": "classification_weighted.precision.factor", "title": "Precision", "concept": [ "Machine learning performance evaluation" ], "topics": [ "weighted.precision.factor" ] }, { "page": "regression_weighted.rae.numeric", "title": "Relative Absolute Error", "concept": [ "Machine learning performance evaluation" ], "topics": [ "weighted.rae.numeric" ] }, { "page": "classification_weighted.recall.factor", "title": "Recall", "concept": [ "Machine learning performance evaluation" ], "topics": [ "weighted.recall.factor" ] }, { "page": "regression_weighted.rmse.numeric", "title": "Root Mean Squared Error", "concept": [ "Machine learning performance evaluation" ], "topics": [ "weighted.rmse.numeric" ] }, { "page": "regression_weighted.rmsle.numeric", "title": "Root Mean Squared Logarithmic Error", "concept": [ "Machine learning performance evaluation" ], "topics": [ "weighted.rmsle.numeric" ] }, { "page": "classification_weighted.roc.curve.factor", "title": "Reciever Operator Characteristics", "concept": [ "Machine learning performance evaluation" ], "topics": [ "weighted.roc.curve.factor" ] }, { "page": "regression_weighted.rrmse.numeric", "title": "Relative Root Mean Squared Error", "concept": [ "Machine learning performance evaluation" ], "topics": [ "weighted.rrmse.numeric" ] }, { "page": "regression_weighted.rrse.numeric", "title": "Root Relative Squared Error", "concept": [ "Machine learning performance evaluation" ], "topics": [ "weighted.rrse.numeric" ] }, { "page": "regression_weighted.rsq.numeric", "title": "r^2", "concept": [ "Machine learning performance evaluation" ], "topics": [ "weighted.rsq.numeric" ] }, { "page": "regression_weighted.smape.numeric", "title": "Symmetric Mean Absolutte Percentage Error", "concept": [ "Machine learning performance evaluation" ], "topics": [ "weighted.smape.numeric" ] }, { "page": "classification_weighted.specificity.factor", "title": "Specificity", "concept": [ "Machine learning performance evaluation" ], "topics": [ "weighted.specificity.factor" ] }, { "page": "classification_weighted.zerooneloss.factor", "title": "Zero-One Loss", "concept": [ "Machine learning performance evaluation" ], "topics": [ "weighted.zerooneloss.factor" ] }, { "page": "data_wine.quality", "title": "Wine quality dataset", "topics": [ "wine.quality" ] }, { "page": "classification_zerooneloss", "title": "Zero-One Loss", "concept": [ "Classification", "Machine learning", "Performance evaluation", "Statistical learning", "Supervised Learning" ], "topics": [ "weighted.zerooneloss", "zerooneloss" ] }, { "page": "classification_zerooneloss.cmatrix", "title": "Zero-One Loss", "concept": [ "Machine learning performance evaluation" ], "topics": [ "zerooneloss.cmatrix" ] }, { "page": "classification_zerooneloss.factor", "title": "Zero-One Loss", "concept": [ "Machine learning performance evaluation" ], "topics": [ "zerooneloss.factor" ] } ], "_pkglogo": "https://github.com/serkor1/SLmetrics/raw/HEAD/man/figures/logo.png", "_readme": "https://github.com/serkor1/SLmetrics/raw/HEAD/README.md", "_rundeps": [ "lattice", "Rcpp", "RcppArmadillo" ], "_sysdeps": [ { "shlib": "libblas", "package": "libopenblas0-pthread", "source": "openblas", "version": "0.3.26+ds-1ubuntu0.1", "name": "openblas", "homepage": "https://www.openblas.net/", "description": "Optimized BLAS (linear algebra) library (shared lib, pthread)" }, { "shlib": "libstdc++", "package": "libstdc++6", "source": "gcc", "version": "14.2.0-4ubuntu2~24.04.1", "name": "c++", "homepage": "http://gcc.gnu.org/", "description": "GNU Standard C++ Library v3" }, { "shlib": "libgomp", "package": "libgomp1", "source": "gcc", "version": "14.2.0-4ubuntu2~24.04.1", "name": "openmp", "homepage": "http://gcc.gnu.org/", "description": "GCC OpenMP (GOMP) support library" } ], "_vignettes": [ { "source": "vignette_classification.Rmd", "filename": "vignette_classification.html", "title": "Classification Metrics", "engine": "knitr::rmarkdown", "headings": [ "Computing classification metrics", "Computing weighted classification metrics" ], "created": "2025-03-13 05:14:19", "modified": "2025-06-07 06:41:31", "commits": 3 }, { "source": "vignette_regression.Rmd", "filename": "vignette_regression.html", "title": "Regression Metrics", "engine": "knitr::rmarkdown", "headings": [ "Computing regression metrics" ], "created": "2025-03-13 05:14:19", "modified": "2025-06-07 06:41:31", "commits": 2 } ], "_score": 4.431363764158988, "_indexed": false, "_nocasepkg": "slmetrics", "_universes": [ "fastverse" ], "_binaries": [ { "r": "4.7.0", "os": "linux", "version": "0.3-4", "date": "2026-06-09T14:10:34.000Z", "distro": "noble", "arch": "aarch64", "commit": "f15c4b758a0b4a8160ab0eed3e3d2b43d2d37b16", "fileid": "c292d1648116aef77966985e840ecb2bbc7ef252cc9054dafb8eb4c22a234e2f", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/fastverse/actions/runs/27211276509" }, { "r": "4.7.0", "os": "linux", "version": "0.3-4", "date": "2026-06-09T14:10:30.000Z", "distro": "noble", "arch": "x86_64", "commit": "f15c4b758a0b4a8160ab0eed3e3d2b43d2d37b16", "fileid": "2e9d3574d75a8051e152092be268466ec8fdb04cf9ca15d3fb380679838a28e7", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/fastverse/actions/runs/27211276509" }, { "r": "4.6.0", "os": "linux", "version": "0.3-4", "date": "2026-06-09T14:10:34.000Z", "distro": "noble", "arch": "aarch64", "commit": "f15c4b758a0b4a8160ab0eed3e3d2b43d2d37b16", "fileid": "83ba53378526e3895a408326c71898740906116557a99c0775016c3d518ed85d", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/fastverse/actions/runs/27211276509" }, { "r": "4.6.0", "os": "linux", "version": "0.3-4", "date": "2026-06-09T14:10:28.000Z", "distro": "noble", "arch": "x86_64", "commit": "f15c4b758a0b4a8160ab0eed3e3d2b43d2d37b16", "fileid": "520ac9f1120dcef5154c42d6923744b5263bb8060a9d0acf8fa1efd1f8ec3156", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/fastverse/actions/runs/27211276509" }, { "r": "4.5.3", "os": "mac", "version": "0.3-4", "date": "2026-06-09T14:18:24.000Z", "arch": "aarch64", "commit": "f15c4b758a0b4a8160ab0eed3e3d2b43d2d37b16", "fileid": "5de853545a0cfd74d3e4376dbfb103b51a9730974cbd1d43087e1c63a3577a55", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/fastverse/actions/runs/27211276509" }, { "r": "4.5.3", "os": "mac", "version": "0.3-4", "date": "2026-06-09T14:20:38.000Z", "arch": "x86_64", "commit": "f15c4b758a0b4a8160ab0eed3e3d2b43d2d37b16", "fileid": "7dd4c85e81e0581709f2d216a7ad222528cdc2354a4e3e5a956bb156c719d5fb", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/fastverse/actions/runs/27211276509" }, { "r": "4.6.0", "os": "mac", "version": "0.3-4", "date": "2026-06-09T14:18:18.000Z", "arch": "aarch64", "commit": "f15c4b758a0b4a8160ab0eed3e3d2b43d2d37b16", "fileid": "8042e9be4dc4a812265a72554f91af96a055e66f533ba185d68ed2ce3bcd5f69", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/fastverse/actions/runs/27211276509" }, { "r": "4.6.0", "os": "mac", "version": "0.3-4", "date": "2026-06-09T14:20:50.000Z", "arch": "x86_64", "commit": "f15c4b758a0b4a8160ab0eed3e3d2b43d2d37b16", "fileid": "fe3fe6b4039b9fd6252b62b3954a431afbc003353340dc7e300b0f2281f4a858", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/fastverse/actions/runs/27211276509" }, { "r": "4.6.0", "os": "wasm", "version": "0.3-4", "date": "2026-06-09T14:10:53.000Z", "arch": "emscripten", "commit": "f15c4b758a0b4a8160ab0eed3e3d2b43d2d37b16", "fileid": "7d37ca05e3d1a33b935a02ee301125cbf1e79f35d9dda44cbf9f8f74ca144c2e", "status": "success", "buildurl": "https://github.com/r-universe/fastverse/actions/runs/27211276509" }, { "r": "4.7.0", "os": "win", "version": "0.3-4", "date": "2026-06-09T14:10:11.000Z", "arch": "x86_64", "commit": "f15c4b758a0b4a8160ab0eed3e3d2b43d2d37b16", "fileid": "c6b71dd513a5df7b62feca162491caf694964c2525a4ea7b2b171732a0c2afd3", "status": "success", "check": "WARNING", "buildurl": "https://github.com/r-universe/fastverse/actions/runs/27211276509" }, { "r": "4.5.3", "os": "win", "version": "0.3-4", "date": "2026-06-09T14:09:58.000Z", "arch": "x86_64", "commit": "f15c4b758a0b4a8160ab0eed3e3d2b43d2d37b16", "fileid": "5f8c303e5fe844afec347d9543834b888b232f17dee688f7b60e2d61da78f2c2", "status": "success", "check": "WARNING", "buildurl": "https://github.com/r-universe/fastverse/actions/runs/27211276509" }, { "r": "4.6.0", "os": "win", "version": "0.3-4", "date": "2026-06-09T14:10:05.000Z", "arch": "x86_64", "commit": "f15c4b758a0b4a8160ab0eed3e3d2b43d2d37b16", "fileid": "eab7cc8d47b43f15581c98331637456f9ec52903ae45d0967ab01c6255bf0a47", "status": "success", "check": "WARNING", "buildurl": "https://github.com/r-universe/fastverse/actions/runs/27211276509" } ] }