Result for 006B5F362000778E87B7B12D48627274A3E4B35E

Query result

Key Value
FileName./usr/lib64/python3.9/site-packages/sklearn/manifold/__pycache__/locally_linear.cpython-39.pyc
FileSize644
MD5DEDC0777030F99F44CDC0C1F639A0302
SHA-1006B5F362000778E87B7B12D48627274A3E4B35E
SHA-256D240DFCE14EAB3FE01EE5590D047114D679B5C91F7BEE5504CEF9609C85D9ED0
SSDEEP12:Qi/K2ZILsS/ADJ5leRHhv1nHA20vGeEiuyr6hQBlk6MRcsc3gDn:Q0Wsb3eRJ1nweeERfh0a6Aqy
TLSHT167F07D53170B2771DEE176F6245646214AF14A23674D82436F98AD0F75063DA1509A6C
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
MD5696C5D9A72AED7B4961D2FAD4DE3EE0F
PackageArchx86_64
PackageDescription Scikit-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
PackageNamepython3-scikit-learn
PackageRelease2.fc33
PackageVersion0.23.1
SHA-1E21018ED668BE7CE20E7709EAAD62C5809D4391B
SHA-25626FBA8D670F9F85130EC5884584D277A959B74FCD23704CC9E39AE4FB490B51F