Key | Value |
---|---|
FileName | ./usr/lib64/R/library/hmeasure/NAMESPACE |
FileSize | 334 |
MD5 | 91110BC273420FEDF2A8952DEBC21078 |
SHA-1 | 048DBF760E3DF5EDB3310762C92E7760ECD8EB3E |
SHA-256 | 3869C9B0B34A62EAEE134FC34DB8812896CA045A256965A299F5FAC2B5F7667F |
SSDEEP | 6:S3m+0FKK1iodRaWKJMRY+gMRngsManoVD1UgXZ2oDjOfdRRcPvRedFv:8mhWodRaW9R5gMRgYoVD1LZ2oDKfdLcS |
TLSH | T1E6E0C24FA2FAC024AFCF38F05E2076720030914CF719646B886BE73DD74226A003E866 |
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 |