Result for 79D2A817F0AF635EAE5511F8512D89BBE9B96B50

Query result

Key	Value
MD5	A3B0BF6DA049BC153C311CF8545E1DA1
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	python-scikit-learn
PackageRelease	2.fc22
PackageVersion	0.16.0
SHA-1	79D2A817F0AF635EAE5511F8512D89BBE9B96B50
SHA-256	1EA343E02ADA3862F436A8769CF3A2DF2148AD3EB9F117447C3DEE19DA848E02
hashlookup:children-total	944
hashlookup:trust	50

Network graph view

Children (Total: 944)

The searched file hash includes 944 children files known and seen by metalookup. A sample is included below:

Key	Value
FileName	./usr/lib64/python3.4/site-packages/sklearn/cluster/hierarchical.py
FileSize	40213
MD5	8445D44F4F9E4D4112DCC21A36D037F7
SHA-1	000C3C854269C2922BE1C06595F3E880851D30D3
SHA-256	E9F414A812CF50C6FC8061E0C0D971798F41FA8326ABEF670BFE139617C27AB2
SSDEEP	768:b6CfhXuUcGwQogk2J3If3V4Spty5kccGwfoPr22J4HDGV4r2o2KKkPkGwkelh7pD:b64eUPzIf3V4Spty5kcP1rqHDGV4r2o2
TLSH	T19B03B722660423715B8790924E7F91A7E34044DF9F5320793DAD92686F12B68F2FFBC9

Key	Value
FileName	./usr/lib/python2.7/site-packages/sklearn/gaussian_process/correlation_models.pyo
FileSize	8295
MD5	4C04A0D332C6CE2A87C0F758519DB7F1
SHA-1	00ED2C175AE4DE1B95EE52D621F0B66DC232F0DD
SHA-256	558CC9AEC64B99BDB49359B6BFC9A7641265A54DDFBBA593226BE201D9B6E043
SSDEEP	192:mCFI85Qp5v2WV56PvL2TTxmoKvGrskFZjvwa65wx1vw3j5rdRsB:rFIfvvuvL2TQvuphvwapvw3u
TLSH	T1C80200829BA9076AE1D281B074B26403D965D07B7A92AB00369CF4B43FD1F70D93F3C9

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/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/lib/python2.7/site-packages/sklearn/tests/test_kernel_approximation.pyo
FileSize	7209
MD5	F470BD469EC17372AFD69BE10E698704
SHA-1	01360A854772AEB6E03F0F672B31B544C33BB44F
SHA-256	9458D11DB183D8FC2E71C871A516B0D6418B8236BA051EFF71086D51945AA00C
SSDEEP	192:y+w8J8JkU9iVrSTf3eEy5a/+e1QySlMiQ3NhbIFqI+81:yAyfAOTxy5uQySJElp81
TLSH	T1F9E14281A3EA8E47E0B02A3C60F0531BECA5F576A500776133FCE6793AC9369D51E385

Key	Value
FileName	./usr/lib64/python3.4/site-packages/sklearn/neighbors/nearest_centroid.py
FileSize	7219
MD5	3F05ED5457FCF69C422C4EB5F5D86CA4
SHA-1	0164D287CCF459DEB314C9B84916163D69BEEE13
SHA-256	0A2CAF710C753B10E6D10F95CF1D2E91CD430CCF9CF37EB0B95A300A138040D6
SSDEEP	192:zLmCsu7Ej7Mvse9Du2izWTOgxMW2MB7lxXB:/maELeZu2iSO+32MB71
TLSH	T1D5E1B5166B061B3AC787C46396CD495BB746863B9364182E3CFD52642F0142CA3FFDD9

Key	Value
FileName	./usr/lib/python2.7/site-packages/sklearn/externals/joblib.pyo
FileSize	909
MD5	4946AAEF8F439639290D99618F3CA383
SHA-1	0167D0D3BED46EBE2D05F41C241FC690FC14DB8F
SHA-256	7EAAA90E98ED3385354F73CE073D861F9F4CD3C0A5A9B7EE87D20A67E319C16C
SSDEEP	24:IbvfuWggXOqstUA/Bjha2ezkRrxsIVzPMteWQt1yQb0saLj:cZOqix9apzkRZEtJQt1yQb0tH
TLSH	T164110080873A4263D66E863778150143C6E5B47B3652C3A81BD9FAF776DC30485263CD

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

Key	Value
FileName	./usr/lib/python2.7/site-packages/sklearn/random_projection.pyo
FileSize	21136
MD5	7525ED7A2E3FFB7BEA72E5D8BFCBE524
SHA-1	01BCC30F2CABF8291E4CD1301AF1B7B381BEACE5
SHA-256	836BCCBB70D337329BF93D1D00BC92AF295B675EAFDF1C2DA95248F016033F8C
SSDEEP	384:iQIVMlqFdVdMrFuODgYZFgxv7uW9PyM8fgwf824Tb//INHoVs4yJ0OmarE8V1tTL:NImKdVKrFuODdZFgv7uW9qMtR9TcNHoU
TLSH	T1329295017B84437AC2E28571A6F66943D6F9F0B7A682665234ACC0793FE1535A13F3CE

Key	Value
FileName	./usr/lib/python2.7/site-packages/sklearn/utils/sparsetools/__init__.pyo
FileSize	348
MD5	AEDF64400C93884A5EB3283CAA0050CB
SHA-1	01FF6B7936B5F36986F2E099507E22FD3B5FE09E
SHA-256	E58FEFA2D1A5B64963422420188006AAA143914F095F74E444F667344B22F477
SSDEEP	6:Ij/k2lBETS/x+LyXLxsOBo38L44klT/UVlle29Y3xmDrkA8eiQRajz:IbkCCOlb3+3a44klLUV/e2fcpQgjz
TLSH	T1C6E026C4D26C1B27C5FE8236A411560381E8D973665305823A4860BE2DD8616863B68E