Result for 00ED2C175AE4DE1B95EE52D621F0B66DC232F0DD

Query result

Key Value
FileName./usr/lib/python2.7/site-packages/sklearn/gaussian_process/correlation_models.pyo
FileSize8295
MD54C04A0D332C6CE2A87C0F758519DB7F1
SHA-100ED2C175AE4DE1B95EE52D621F0B66DC232F0DD
SHA-256558CC9AEC64B99BDB49359B6BFC9A7641265A54DDFBBA593226BE201D9B6E043
SSDEEP192:mCFI85Qp5v2WV56PvL2TTxmoKvGrskFZjvwa65wx1vw3j5rdRsB:rFIfvvuvL2TQvuphvwapvw3u
TLSHT1C80200829BA9076AE1D281B074B26403D965D07B7A92AB00369CF4B43FD1F70D93F3C9
hashlookup:parent-total1
hashlookup:trust55

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Parents (Total: 1)

The searched file hash is included in 1 parent files which include package known and seen by metalookup. A sample is included below:

Key Value
MD5A3B0BF6DA049BC153C311CF8545E1DA1
PackageArchs390
PackageDescriptionScikit-learn integrates machine learning algorithms in the tightly-knit scientific Python world, building upon numpy, scipy, and matplotlib. As a machine-learning module, it provides versatile tools for data mining and analysis in any field of science and engineering. It strives to be simple and efficient, accessible to everybody, and reusable in various contexts.
PackageMaintainerFedora Project
PackageNamepython-scikit-learn
PackageRelease2.fc22
PackageVersion0.16.0
SHA-179D2A817F0AF635EAE5511F8512D89BBE9B96B50
SHA-2561EA343E02ADA3862F436A8769CF3A2DF2148AD3EB9F117447C3DEE19DA848E02