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author | Ricardo Wurmus <rekado@elephly.net> | 2024-01-18 14:27:37 +0100 |
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committer | Ricardo Wurmus <rekado@elephly.net> | 2024-01-18 16:01:54 +0100 |
commit | f6f48b13e5b182a3284d15ff626bdb5531c69e03 (patch) | |
tree | a5c2c29c5e1b4e40e0c012bd59ee912d07512a0d /gnu/packages | |
parent | 48b5e885182738fe28bed2d1b45e91be95dce67c (diff) | |
download | guix-f6f48b13e5b182a3284d15ff626bdb5531c69e03.tar.gz guix-f6f48b13e5b182a3284d15ff626bdb5531c69e03.zip |
gnu: Add r-rocit.
* gnu/packages/cran.scm (r-rocit): New variable.
Change-Id: I255db21624dd3684d38748ce42ce71e8fa9fb73b
Diffstat (limited to 'gnu/packages')
-rw-r--r-- | gnu/packages/cran.scm | 29 |
1 files changed, 29 insertions, 0 deletions
diff --git a/gnu/packages/cran.scm b/gnu/packages/cran.scm index 101d4fc1ca..d6fccb125e 100644 --- a/gnu/packages/cran.scm +++ b/gnu/packages/cran.scm @@ -1529,6 +1529,35 @@ allows transformation of geographic coordinates from one projection and/or datum to another.") (license license:gpl2))) +(define-public r-rocit + (package + (name "r-rocit") + (version "2.1.1") + (source + (origin + (method url-fetch) + (uri (cran-uri "ROCit" version)) + (sha256 + (base32 "0sd6ckh7k8aqwhzzp3qff6g7d03klbr0mbp403pib3823c8pqa55")))) + (properties `((upstream-name . "ROCit"))) + (build-system r-build-system) + (native-inputs (list r-knitr)) + (home-page "https://cran.r-project.org/package=ROCit") + (synopsis "Performance Assessment of Binary Classifier with Visualization") + (description + "Sensitivity (or recall or true positive rate), false positive rate, +specificity, precision (or positive predictive value), negative predictive +value, misclassification rate, accuracy, F-score---these are popular metrics +for assessing performance of binary classifiers for certain thresholds. These +metrics are calculated at certain threshold values. @dfn{Receiver operating +characteristic} (ROC) curve is a common tool for assessing overall diagnostic +ability of the binary classifier. Unlike depending on a certain threshold, +area under ROC curve (also known as AUC), is a summary statistic about how +well a binary classifier performs overall for the classification task. The +ROCit package provides flexibility to easily evaluate threshold-bound +metrics.") + (license license:gpl3))) + (define-public r-rorcid (package (name "r-rorcid") |