Result for 3E722EE4741DDEA39E448193F68CA755F01AA67F

Query result

Key Value
FileName./usr/lib64/R/library/hmeasure/doc/hmeasure.Rnw
FileSize38596
MD53AC86171963E2B2578C089552C5551E6
SHA-13E722EE4741DDEA39E448193F68CA755F01AA67F
SHA-2568A70A5E50547E1C0CE845FF9B94691135BCC8450D7F1749A7D400963BEFC706B
SSDEEP768:qBCI7Z32Jj4+ESN6KI2XTsjiBU31y1s4uoi9oMirc0RfrafzlMYX2:qBCcZUFEvamyy/kfrwzX2
TLSHT10F03D81773000B770B630161AE0E52D6B33A81BCE762995878FEC4B92246C75C7BB6DE
hashlookup:parent-total5
hashlookup:trust75

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Parents (Total: 5)

The searched file hash is included in 5 parent files which include package known and seen by metalookup. A sample is included below:

Key Value
MD516F407E9253555312E844C97E4B33F6B
PackageArchx86_64
PackageDescriptionClassification performance metrics that are derived from the ROC curve of a classifier. The package includes the H-measure performance metric as described in <http://link.springer.com/article/10.1007/s10994-009-5119-5>, which computes the minimum total misclassification cost, integrating over any uncertainty about the relative misclassification costs, as per a user-defined prior. It also offers a one-stop-shop for other scalar metrics of performance, including sensitivity, specificity and many others, and also offers plotting tools for ROC curves and related statistics.
PackageNameR-hmeasure
PackageReleaselp153.2.1
PackageVersion1.0.2
SHA-18B338D03650E85312D4FC9D890488D7C459E20E0
SHA-25698C6A74BC879C364AEB8F800B22A100D8024E89789A2A79AB86E3300C5C2B48F
Key Value
MD5F45B2A6D144BA006D452DE3743D2D7DF
PackageArchx86_64
PackageDescriptionClassification performance metrics that are derived from the ROC curve of a classifier. The package includes the H-measure performance metric as described in <http://link.springer.com/article/10.1007/s10994-009-5119-5>, which computes the minimum total misclassification cost, integrating over any uncertainty about the relative misclassification costs, as per a user-defined prior. It also offers a one-stop-shop for other scalar metrics of performance, including sensitivity, specificity and many others, and also offers plotting tools for ROC curves and related statistics.
PackageNameR-hmeasure
PackageReleaselp152.2.6
PackageVersion1.0.2
SHA-1CA4179E31D3E67D060E56A96F3F217CD9401DCF6
SHA-2560543EFE97A14516E03E318C14FD7982055DADF572DA52709D4A194827E01EE01
Key Value
MD51F18EE8B6B1638EC1DF08EABFF0C9A4C
PackageArchx86_64
PackageDescriptionClassification performance metrics that are derived from the ROC curve of a classifier. The package includes the H-measure performance metric as described in <http://link.springer.com/article/10.1007/s10994-009-5119-5>, which computes the minimum total misclassification cost, integrating over any uncertainty about the relative misclassification costs, as per a user-defined prior. It also offers a one-stop-shop for other scalar metrics of performance, including sensitivity, specificity and many others, and also offers plotting tools for ROC curves and related statistics.
PackageNameR-hmeasure
PackageRelease2.21
PackageVersion1.0.2
SHA-198D93B77D81B839F850F0086AF5C68ABCAB48D36
SHA-2565B6ABB6BCF08F076385F4F24968553532091DF8357ED654EC7A04B991CB99CFC
Key Value
MD595054B3EAC7B7D74A289FAEB9FBD7E06
PackageArchx86_64
PackageDescriptionClassification performance metrics that are derived from the ROC curve of a classifier. The package includes the H-measure performance metric as described in <http://link.springer.com/article/10.1007/s10994-009-5119-5>, which computes the minimum total misclassification cost, integrating over any uncertainty about the relative misclassification costs, as per a user-defined prior. It also offers a one-stop-shop for other scalar metrics of performance, including sensitivity, specificity and many others, and also offers plotting tools for ROC curves and related statistics.
PackageNameR-hmeasure
PackageReleaselp153.2.3
PackageVersion1.0.2
SHA-1E6D57A31EF46B5A52A4EC6E00B3F7A2A03FB198A
SHA-2566400CEB81B653E96BABCF5EE399AD38BE36C6A1B73E6F4BDFEBC50FCC22AD275
Key Value
MD5F5B2F4CA55DF4F927C501D41D53BBB82
PackageArchx86_64
PackageDescriptionClassification performance metrics that are derived from the ROC curve of a classifier. The package includes the H-measure performance metric as described in <http://link.springer.com/article/10.1007/s10994-009-5119-5>, which computes the minimum total misclassification cost, integrating over any uncertainty about the relative misclassification costs, as per a user-defined prior. It also offers a one-stop-shop for other scalar metrics of performance, including sensitivity, specificity and many others, and also offers plotting tools for ROC curves and related statistics.
PackageMaintainerhttps://www.suse.com/
PackageNameR-hmeasure
PackageReleaselp154.2.1
PackageVersion1.0.2
SHA-1806511F0620EE336B8D1919B77A382C8158A14B1
SHA-256EC99CECAD5C4C6B0A1DB5CE411077EFCDBDE8D556E5D9FF35153E9B7D46020E4