| Key | Value |
|---|---|
| FileName | ./usr/share/doc/mlpack-3.2.2/html/structmlpack_1_1tree_1_1IsSpillTree_3_01tree_1_1SpillTree_3_01MetricType_00_01StatisticType_00_0eb5e0ce9f3404a5f014de8c682020c7a.html |
| FileSize | 7346 |
| MD5 | B472597CBDA092E2825EBFDA99DEDD0A |
| SHA-1 | 005B11DD8D775BC0C3429B345828869B3A71C020 |
| SHA-256 | 5D73C40D676E7B1CE31EAC4201B759895A8A14E79FE684FAFCE0D635DB0326F7 |
| SSDEEP | 96:xXumrMu9bo1HqqTGYnZ5+toIDsdRozX52uoz8C8f89lFWFq/VZ1zZ835zZqdrb9F:1umrZcCTsdKO8Q+irpF |
| TLSH | T1ECE1A66928D74133C2FB46CAB6F3EB35B0D18029C7440814B5FC2A6E1785F89B57B62B |
| hashlookup:parent-total | 4 |
| hashlookup:trust | 70 |
The searched file hash is included in 4 parent files which include package known and seen by metalookup. A sample is included below:
| Key | Value |
|---|---|
| MD5 | 187FB3258DB56330FE8AAF09BCFF57F4 |
| PackageArch | x86_64 |
| PackageDescription | mlpack is a C++ machine learning library with emphasis on scalability, speed, and ease-of-use. Its aim is to make machine learning possible for novice users by means of a simple, consistent API, while simultaneously exploiting C++ language features to provide maximum performance and maximum flexibility for expert users. mlpack outperforms competing machine learning libraries by large margins. This package provides the Doxygen-generated documentation for mlpack. |
| PackageMaintainer | Fedora Project |
| PackageName | mlpack-doc |
| PackageRelease | 1.el7 |
| PackageVersion | 3.3.0 |
| SHA-1 | CB94710D0E20530AA6287667473456123733362E |
| SHA-256 | 277FD5CF1A4F3E0650FFB1DC271BA252827EF85DC47D319080E17402E7279138 |
| Key | Value |
|---|---|
| MD5 | 373261FB21C511D4C63C3F90DFA2A1F5 |
| PackageArch | x86_64 |
| PackageDescription | mlpack is a C++ machine learning library with emphasis on scalability, speed, and ease-of-use. Its aim is to make machine learning possible for novice users by means of a simple, consistent API, while simultaneously exploiting C++ language features to provide maximum performance and maximum flexibility for expert users. mlpack outperforms competing machine learning libraries by large margins. This package provides the Doxygen-generated documentation for mlpack. |
| PackageMaintainer | Fedora Project |
| PackageName | mlpack-doc |
| PackageRelease | 1.el7 |
| PackageVersion | 3.2.2 |
| SHA-1 | D9FD358E838F7398010C444F7CCFEFB8DF800F5B |
| SHA-256 | 3979C803DB85D58862240AAB86A5834F5A7303CBAEF9324EAD59CEA4D8892C39 |
| Key | Value |
|---|---|
| MD5 | 55F571157BB700A5A4A09FEE6A8F6E56 |
| PackageArch | ppc64le |
| PackageDescription | mlpack is a C++ machine learning library with emphasis on scalability, speed, and ease-of-use. Its aim is to make machine learning possible for novice users by means of a simple, consistent API, while simultaneously exploiting C++ language features to provide maximum performance and maximum flexibility for expert users. mlpack outperforms competing machine learning libraries by large margins. This package provides the Doxygen-generated documentation for mlpack. |
| PackageMaintainer | Fedora Project |
| PackageName | mlpack-doc |
| PackageRelease | 1.el7 |
| PackageVersion | 3.2.2 |
| SHA-1 | B9E4D0C198378D99A34735C901F2C4CC02FEB399 |
| SHA-256 | 4ECCABA7A2872F733F7570572A12596CF43A2898CF80AF45FFA7BA5A75C9E6BA |
| Key | Value |
|---|---|
| MD5 | 8500E090D93ABB536727EC358AA6A8DC |
| PackageArch | ppc64le |
| PackageDescription | mlpack is a C++ machine learning library with emphasis on scalability, speed, and ease-of-use. Its aim is to make machine learning possible for novice users by means of a simple, consistent API, while simultaneously exploiting C++ language features to provide maximum performance and maximum flexibility for expert users. mlpack outperforms competing machine learning libraries by large margins. This package provides the Doxygen-generated documentation for mlpack. |
| PackageMaintainer | Fedora Project |
| PackageName | mlpack-doc |
| PackageRelease | 1.el7 |
| PackageVersion | 3.3.0 |
| SHA-1 | 0649F9774CC719B07D00310FA65A705FBA6AD36E |
| SHA-256 | 9DB007F997C0C7DC5E0CD0E0F5E770655835B6ABF01D29572906C5D2ED8EF9AE |