Result for D485DF7805397141626C57B45FA87B307DED3B19

Query result

Key	Value
MD5	7CFEEC4C24C01483E892298BFA5817D3
PackageArch	ppc
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	3.fc20
PackageVersion	0.14.1
SHA-1	D485DF7805397141626C57B45FA87B307DED3B19
SHA-256	E77BC6E49AE458FE84B1826BC4E3BCB5103DFA740B2FA78B6FD8A8E53605F702
hashlookup:children-total	801
hashlookup:trust	50

Network graph view

Children (Total: 801)

The searched file hash includes 801 children files known and seen by metalookup. A sample is included below:

Key	Value
FileName	./usr/lib/python3.3/site-packages/sklearn/__pycache__/naive_bayes.cpython-33.pyo
FileSize	24015
MD5	A7EEE95EB08872ECE185B63E6B1652F1
SHA-1	0008ACC2F9FB3883984AB04B7E33A01AE5298BB1
SHA-256	6AD7FA7BA1DB845A5E4C81F95083B1B053E0CC7E2519119B0223CD27109DCA28
SSDEEP	384:MGLtNi4yqMDoxE3zpoXxPR5HiDiOasKi/Di24PkOzCM/fEO8K0jKYF3FlsMvZiG8:MG5gdqkoxE1gnkH7fakOzCAfEnpLVlsT
TLSH	T159B2D649AF2D4AFBD463877220F10146DE62A6BB8A841B0134FEE5712FC1B76173F649

Key	Value
FileName	./usr/share/doc/python-sklearn-doc/examples/linear_model/plot_ols_ridge_variance.py
FileSize	2032
MD5	44A08C8EAB78FA8522617D143280CE43
SHA-1	002D35237E1045669AE711D219C5C7E2C828DF64
SHA-256	DF23A76B9DA4857633A934C3CDEAC1FB3F1C3C0BFA5266F2CF148F22CC3F7240
SSDEEP	48:4YOa+3VOPSAN5mAOxGwq0JcrsyPAhpa2b7TyJANfeK6AK/l:4YOTlvsmAOxGwvJdyP7ifmWeK6Ail
TLSH	T15841861B62861B73A337942DBDB9329C7351409F79427CA57BFC61085F8172C0EB94B5

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/examples/exercises/plot_iris_exercise.py
FileSize	1577
MD5	3CEE1240FBA2960897069B76B5637772
SHA-1	0116272B06B5037C5FC6E48E289CAD5FC1E6CC61
SHA-256	BE809F9603D572D38F9B2B5C30FDDBC3865711F28480FD46C2EDFED3DB78BC83
SSDEEP	24:/AX9SV6wq4Vxknvg059WbkKX52BrpH2sCU5tkLtmGvItyG4bxpZNbH/D:IXcVVVqrKX5m8lMtggGPbxfNz/D
TLSH	T1F031201A904E337213C790BD82EB29846B5366234B44687A777DB7D1DF02764F239942

Key	Value
FileName	./usr/lib/python3.3/site-packages/sklearn/cluster/tests/__pycache__/test_k_means.cpython-33.pyo
FileSize	31295
MD5	8CD2C2355E65A5A952CFBA8938552937
SHA-1	0214DC1B2E3E291B4CBBF42E031B2FA2AD13644F
SHA-256	562C80258290AB00BEDC1ADD76F7C3139BEBE74AC9BFBF012306F28CE80E8EE2
SSDEEP	768:UAv0v5P1dw5o8AsjzV7loiu5DthtW7p5dRZPerGTo15OR+VAEFD5E5bRI9Pr5UmV:jMvzOwiOwYb55lwtK+Ki/3lBm9Ga
TLSH	T139E2429153FF8BD3D8F1B6B868281322DE52F8B29D90AF412770B07C25C663E356B546

Key	Value
FileName	./usr/lib/python3.3/site-packages/sklearn/datasets/__pycache__/species_distributions.cpython-33.pyo
FileSize	9069
MD5	F09E18D945345C00F8412C343CC3FFB9
SHA-1	02468E66AB473EF88813B180BAC32F9D16B4C41F
SHA-256	8B4C8CD07F61CD428212F14E89E74E9919B32FCF85784E4F8EA83C518FFC7C6A
SSDEEP	192:zOD9a7u9JXJRJqJ93SJ/NnndFbJpq79Je+qutNJL3TYvRw3TWmJTTq4JOW:M9zj5/+9WpNUH/fYEySTTqAOW
TLSH	T1081272843FAE4BF5D1B156B865791202D763F9AFE2002704729CE0A42F4DF325ABF681

Key	Value
FileName	./usr/share/doc/python-sklearn-doc/examples/plot_rfe_digits.py
FileSize	852
MD5	9103650C2F36397AB88DF835B34D38B5
SHA-1	02C0A867F5D8E9C34607BCE93EF5ABF7C6F495A9
SHA-256	9F282DADA6645094618C0A5BFA1913CC17F1384A2BBEC0B7B7783AB89CBE9928
SSDEEP	12:ilgJr4Y/8OREMeyAMyfbyvmvA9NZfXALqSkAVL/KO5Oe4N6sYD:iqh4E8HyLyTyOEfXALCAVIGh
TLSH	T141011E5D5220B7771DB758B582F5809319F20D3A2341622015A8CA658B82BB6FFF7A43

Key	Value
FileName	./usr/share/doc/python-sklearn-doc/examples/plot_kernel_approximation.py
FileSize	7974
MD5	92E29404D8F074E46F35C40F20766AB8
SHA-1	02FB35C9AF06F6F6872DFFCAAC0A51570D42B6A2
SHA-256	BF5D973C48EC576C568FF9ECFB74EA75395EBF29B4D1C19AB82D210B6A4DDCF4
SSDEEP	96:0X75FrUiJKIiRjQBdLdgooMgFYZygEqTgR/KYIOcITTmpsm51iuPztYi:+75FQiti6KYZkR/KYIOcITq1iuhYi
TLSH	T17CF1E80B20E30B3223B7207C23DC21C7BFA49056E9975A3DF99D8654379AF21E276649

Key	Value
FileName	./usr/share/doc/python3-scikit-learn/examples/ensemble/plot_adaboost_multiclass.py
FileSize	3585
MD5	34017803563CB9F9B635C002523C75AB
SHA-1	0322042E7BF79C438AD29D097C0E77A689587F33
SHA-256	50E1E9107975866013E5FFB4FA9033867E9BB126CC32959A3E9CC4E3E4204164
SSDEEP	96:ir9H8frWUXgINfBhroMYbPXwW/K/oKR6m257TwDLj5dlTn2093:DC3iXR6mp1N
TLSH	T1F07193258A666A3187B96CFECCAC526D3360144C9D22D009B5FD8F300F0BF19ECBA2D4

Key	Value
FileName	./usr/share/pyshared/sklearn/cluster/spectral.py
FileSize	19089
MD5	7F39F2175913371EB02C1FC7AD23163A
SHA-1	03C4601BEAD359C5B92ED2D0FA173AB399D8C9FE
SHA-256	E4FAABA262F99730C34B8078D83DACC8BF18776F391D8A9657004B8524E70BE8
SSDEEP	384:M+X/Q0+fEqCC56so+IRrREezf61red3/YV7i/aD6VHnNW5ajWlFYV7wJC1S/a703:M+X/Q0kEqCC56soTPloret/WW/aD6741
TLSH	T17582D739394262379C87E09289FE20A68364058F8F537455B99DC6281F13E7873BEFD5