Result for 025A975C0C9E72A0C75A0C50E84289B679110F0F

Query result

Key Value
FileName./usr/lib64/python2.7/site-packages/sklearn/manifold/spectral_embedding_.pyo
FileSize15977
MD5C7A0E6A0BD0BEA4B4C15E9AB97D5FBCE
SHA-1025A975C0C9E72A0C75A0C50E84289B679110F0F
SHA-256B6E6523E9237EF3696D2A0AC8DE49B7717FB4408F72C6C52705C15BBD9B5C500
SSDEEP384:Fnhogg6t4gD1PoKGtZRy6KWV+nPH8snOH+j1dV9d888b:btg6t469QZs6d8nPH8snc+jk
TLSHT13672C5247F4683AFC1A1A0B2A4F4158BCF79E4B7C883639135DED1791FD2664E22E385
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
MD50B5B19D9ADFC87C2B935B888AECEA5A7
PackageArchs390x
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
PackageRelease3.fc20
PackageVersion0.14.1
SHA-1FADF2C294EDD6D3D16374617A9DA1CD8A4DBA9F4
SHA-256E15C9C9E57B5AA8607BE3DA4C6AA16C5F61E8CA7B5B1C3F78AB81819AEB039A5