Result for 87B048B276C5113C9D6CD82A58607CB427813E09

Query result

Key	Value
MD5	2FC7ADC96133810C79BC3A169983D8D2
PackageArch	s390
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.
PackageMaintainer	Fedora Project
PackageName	python3-scikit-learn
PackageRelease	1.fc21
PackageVersion	0.15.2
SHA-1	87B048B276C5113C9D6CD82A58607CB427813E09
SHA-256	36513B4B329827FFDE380318D76D72DB22C7612C6425AD54CCA3D29BBF3EE407
hashlookup:children-total	906
hashlookup:trust	50

Network graph view

Children (Total: 906)

The searched file hash includes 906 children files known and seen by metalookup. A sample is included below:

Key	Value
FileName	./usr/lib64/python3.4/site-packages/sklearn/ensemble/tests/test_forest.py
FileSize	17601
MD5	856C9EB5C6357A8E978BB27ED478B14D
SHA-1	0001980ED073FFA12C4D97EE33F9FC4D4A9FF043
SHA-256	95CDF4DE2328FC18906E92054FE52629B8B6B99CEF8992750C9EA14D9533FA72
SSDEEP	384:RmH3A2etKtuw8ixVT17yl8iMX5nITJojVpKv+66wLoVE/wpL+:RmH3A/tKtuw9xVT17yl8NX5nITJojVpu
TLSH	T18482D703F8960D595B53297E24DE510827956B1B860818753EFFD0086F9462CB3FBBBE

Key	Value
FileName	./usr/lib/python3.4/site-packages/sklearn/decomposition/tests/__pycache__/test_dict_learning.cpython-34.pyo
FileSize	7500
MD5	5FDA9031C6EF02E0B13AEDFF3070C30A
SHA-1	0004D84127224BC5A57928D1DA62885A7A655DAF
SHA-256	3D004C18B08DD9329871A902037E1255A55F4F8F2E0A6A12D52176F744043E10
SSDEEP	192:CJEe+LqI5pXa2VdOPXs0XdYHqfNKnO5qy2d888S8y:CqHLxpa2VdOPXsVKf4nOgy2d888S8y
TLSH	T17AF12195A7C2CA9FF860F1B8A434131D8EBAF6997F0627116AB1E03C3FD07442C27245

Key	Value
FileName	./usr/lib64/python3.4/site-packages/sklearn/linear_model/ransac.py
FileSize	13952
MD5	67B38A5B19534C15626BEDDA27CE70D0
SHA-1	000C0BD44626C1E94A98B9CB8615101BC35C180F
SHA-256	526176561F560882ECAE0B67F451191EBFC36F7E9228B327F61452F553983492
SSDEEP	192:1axKzOGnKFnGWjPfIAeMl0Bgox2WGZHO6qWKNRKES6dIhBNRERZCoNbk7A:oK68KRTfIAXkaHRKS6aBsRZhb7
TLSH	T17F52940568203B374A87B5B068DE010BC77918A79686A4757CFCC3AD1F6297873ADBD8

Key	Value
FileName	./usr/lib/python3.4/site-packages/sklearn/utils/tests/__pycache__/test_murmurhash.cpython-34.pyo
FileSize	3173
MD5	9EB139FD66B72CD97A13F37EB597C6A1
SHA-1	008D4761AA1DC0568151D0EAABCEF4EC8BC7C15F
SHA-256	1FE9BAADA5B056281178D004B59A7FC44387CFFE9EA9DABDAB3E580247AB13B2
SSDEEP	96:HClzhHtg2mxZmYhrv3Vmm8Wq/qqj2H0Jco:HClNHxmxZmYhxmm8/2HE
TLSH	T1A561CC9057D2098FE698F1FBB17413189EF2F45A3F05E7461BB0D53E6AD4B182C2A2C9

Key	Value
FileName	./usr/lib/python3/dist-packages/sklearn/utils/sparsetools/_graph_validation.py
FileSize	2407
MD5	6CCA3A2DFA57FF6AF3CF3A27AE22F209
SHA-1	01070C25205C477A297A7CCE48DA78871F64DD2C
SHA-256	298C9425EE8888DD03C6A32021051C1ACE1D8C45775B277F0095589690515DD8
SSDEEP	48:PLdf167rziXSwtpF8AyEv9iVfkZY2MiV8K2pq:DL6fep8AJYVfkZLFKtpq
TLSH	T1FE41FE25932D0564D16380E48C83A70E1AD8F6073F67242DF4EEBC682F3861C63257BD

Key	Value
FileName	./usr/lib/python3.4/site-packages/sklearn/tests/__pycache__/test_isotonic.cpython-34.pyo
FileSize	8823
MD5	678FD105DDD6B1630E61A35E485E357E
SHA-1	010A5C3D05166E42F3F7616CB066689AC9073A12
SHA-256	F920F9ACA16BD89D7A62DA9CA28F7DEDFFF02F7E83D3EB05813E29B07FEC4764
SSDEEP	192:SLfQLDaZ8CrgaqaZX30ZQsomzfcpnKZ8ZgvZDZzIZMyi1Y6leGQT0:tLDaZ8CrgpwX33Wzfc4y6vxxIvi26AGr
TLSH	T1B102C981A7C28A5FF821F2B9A43463118FB7F41A3F85BB1957B1D4BD3FC17441A16288

Key	Value
FileName	./usr/share/doc/python-sklearn-doc/stable/_downloads/plot_polynomial_interpolation.py
FileSize	1895
MD5	A4CC2943F64D2730EF80B9504C583D19
SHA-1	011BDEF5443BE65B5EC29C9D37FCEEC7206429FA
SHA-256	2B12D9E9919C21B4BFF58007AB9F645B717AE7749E79099AFBB8B253B5A3ABFC
SSDEEP	48:3b/2fr4glFa11YCuArC18AlcCxaD+1sozVGsA9MGNr:z0lAO18gcCE+BgPr
TLSH	T15541B9092E55E82107364074B6F898616E19046EAE8305663DCDBE301B42B0F3D3BF47

Key	Value
FileName	./usr/share/doc/python3-scikit-learn/examples/cluster/plot_cluster_comparison.py
FileSize	4865
MD5	919283D95801BDB1582E6768ADC62A65
SHA-1	0145D31CB950A8CC679300AF4CF93EC48DE5D612
SHA-256	64C861D3DC5FE9F11F44F2AA5A86FF15BEB60B26B7974895663F37DC729039C3
SSDEEP	96:hLrD8Hd/MIsALpqtjAFejIHXSNIuGytASwTgSNexmDDz4bW:h4nVBgZ/6tLQW
TLSH	T176A1857167126117EF93B09A4EB751E837946057075028AAB52CC3254F0BB3CB3F2B9B

Key	Value
FileName	./usr/share/doc/python3-scikit-learn/examples/exercises/plot_cv_digits.py
FileSize	1207
MD5	C21A69A2BC54F263E69035C048095865
SHA-1	016D65381370139D98DCC375AACCF083CD195B82
SHA-256	657225AA5357703DBAC9E250E5690997774CA4C566BC32D257203E93FCAB5E17
SSDEEP	24:akV7BmSxOgUWqNqag5YEA5BRklGiVQ+zAsyPs1J:akaSVUNJEMBRkbuWyOJ
TLSH	T1B621DC0CBAA6B2780B9284B4FC44507137E393106708683E78ABDC6D5646F372B61CB2

Key	Value
FileName	./usr/share/doc/python-sklearn-doc/stable/_downloads/plot_swissroll.py
FileSize	1446
MD5	6C764C92907310B7717595E840304798
SHA-1	0193A74906128D26183FB66001B61CA5D447B865
SHA-256	5D7791C51D76DD46308EE5B4B799509831C1EEDC2D767C39B78E7E98A39B066D
SSDEEP	24:x2RAnm7PXQ2KQsFe3M/MDyC5NJYTC4aeujm5tSU3+LVJU3+PbYY1+BZjs:xEAn12KED3JLe0atSfJNYYqs
TLSH	T116313F1C2E07B27697A2F0E83E6417DDEB515A009F2044F8B83D68F45381B7CB82D51B