Result for 0066D563D4F7C98AF9889C0C64846DEAABF97DE8

Query result

Key Value
FileName./usr/lib64/python3.5/site-packages/sklearn/decomposition/tests/__pycache__/test_sparse_pca.cpython-35.pyc
FileSize5366
MD5ADDBD9654E580328D9728C47035E6D49
SHA-10066D563D4F7C98AF9889C0C64846DEAABF97DE8
SHA-256CC76E37B86EEC4B54915A71475840EDBA44FDAF5065ECDE968B96C2B7A04AC3E
SSDEEP96:68tIy3+0nDCX1irQcCOdBHQOQQJtvlY1u7vCBLdVyFOBGkZcrgp7rkEYhUHSgg6Z:6k3+cUczJVu1uD8KgGhGt7T888w
TLSHT142B1FD91A7C2CE5FF414F2B9A5B847008EB6F84A7F01AB495BF1E4383FE5744A427208
hashlookup:parent-total2
hashlookup:trust60

Network graph view

Parents (Total: 2)

The searched file hash is included in 2 parent files which include package known and seen by metalookup. A sample is included below:

Key Value
MD5BCF32221C8DD22DF9CFE204375B750A2
PackageArchppc64
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
PackageRelease4.fc24
PackageVersion0.17.1
SHA-1547DB711D4863545256C4D84E1B956593497B713
SHA-25676E3540F2E6683CF0BC08CBA78A3756E50A04EB5661067EBAA99481A5CAA6759
Key Value
MD50C4F32374415CCDA8D571AA31F3D20B1
PackageArchaarch64
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
PackageRelease4.fc24
PackageVersion0.17.1
SHA-15513BD93A3C3B030CC6500A683EF48326EB21E74
SHA-25613F962CFADEE43B02880D50748E7A8B387D2C1BC7A41D66A0C868B48D85D09C4