Key | Value |
---|---|
FileName | ./usr/lib64/R/library/hmeasure/doc/hmeasure.Rnw |
FileSize | 38596 |
MD5 | 3AC86171963E2B2578C089552C5551E6 |
SHA-1 | 3E722EE4741DDEA39E448193F68CA755F01AA67F |
SHA-256 | 8A70A5E50547E1C0CE845FF9B94691135BCC8450D7F1749A7D400963BEFC706B |
SSDEEP | 768:qBCI7Z32Jj4+ESN6KI2XTsjiBU31y1s4uoi9oMirc0RfrafzlMYX2:qBCcZUFEvamyy/kfrwzX2 |
TLSH | T10F03D81773000B770B630161AE0E52D6B33A81BCE762995878FEC4B92246C75C7BB6DE |
hashlookup:parent-total | 5 |
hashlookup:trust | 75 |
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 |
---|---|
MD5 | 16F407E9253555312E844C97E4B33F6B |
PackageArch | x86_64 |
PackageDescription | Classification 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. |
PackageName | R-hmeasure |
PackageRelease | lp153.2.1 |
PackageVersion | 1.0.2 |
SHA-1 | 8B338D03650E85312D4FC9D890488D7C459E20E0 |
SHA-256 | 98C6A74BC879C364AEB8F800B22A100D8024E89789A2A79AB86E3300C5C2B48F |
Key | Value |
---|---|
MD5 | F45B2A6D144BA006D452DE3743D2D7DF |
PackageArch | x86_64 |
PackageDescription | Classification 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. |
PackageName | R-hmeasure |
PackageRelease | lp152.2.6 |
PackageVersion | 1.0.2 |
SHA-1 | CA4179E31D3E67D060E56A96F3F217CD9401DCF6 |
SHA-256 | 0543EFE97A14516E03E318C14FD7982055DADF572DA52709D4A194827E01EE01 |
Key | Value |
---|---|
MD5 | 1F18EE8B6B1638EC1DF08EABFF0C9A4C |
PackageArch | x86_64 |
PackageDescription | Classification 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. |
PackageName | R-hmeasure |
PackageRelease | 2.21 |
PackageVersion | 1.0.2 |
SHA-1 | 98D93B77D81B839F850F0086AF5C68ABCAB48D36 |
SHA-256 | 5B6ABB6BCF08F076385F4F24968553532091DF8357ED654EC7A04B991CB99CFC |
Key | Value |
---|---|
MD5 | 95054B3EAC7B7D74A289FAEB9FBD7E06 |
PackageArch | x86_64 |
PackageDescription | Classification 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. |
PackageName | R-hmeasure |
PackageRelease | lp153.2.3 |
PackageVersion | 1.0.2 |
SHA-1 | E6D57A31EF46B5A52A4EC6E00B3F7A2A03FB198A |
SHA-256 | 6400CEB81B653E96BABCF5EE399AD38BE36C6A1B73E6F4BDFEBC50FCC22AD275 |
Key | Value |
---|---|
MD5 | F5B2F4CA55DF4F927C501D41D53BBB82 |
PackageArch | x86_64 |
PackageDescription | Classification 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. |
PackageMaintainer | https://www.suse.com/ |
PackageName | R-hmeasure |
PackageRelease | lp154.2.1 |
PackageVersion | 1.0.2 |
SHA-1 | 806511F0620EE336B8D1919B77A382C8158A14B1 |
SHA-256 | EC99CECAD5C4C6B0A1DB5CE411077EFCDBDE8D556E5D9FF35153E9B7D46020E4 |