Key | Value |
---|---|
MD5 | 70788DF0D009635CFCC2D7B6CEBA420E |
PackageArch | ppc64le |
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.fc23 |
PackageVersion | 0.16.1 |
SHA-1 | 9F75AC393E549EE0B92F281186271B7049B01224 |
SHA-256 | 5A59C3C43D6F64A95FCB5D4CF1DF85EDCD63DF549B0638B1BD63E870BD1CF02B |
hashlookup:children-total | 944 |
hashlookup:trust | 50 |
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/lib64/python3.4/site-packages/sklearn/utils/sparsetools/__pycache__/setup.cpython-34.pyo |
FileSize | 756 |
MD5 | A262C7C072E6F66264D2E341231B3DD2 |
SHA-1 | 007F93CB4A9ADDE3371D508F06F6567DEB826C86 |
SHA-256 | A2F96A668DE2D5020E3184AB2C08EB012C8FAF8741C08F597D97E3F7772AC99C |
SSDEEP | 12:+jXC2Muodomb4IWmTkPM2fFuKF3RuqMiMWAgAAR0VzGGDJLfxsMqhjw1MiMlL:eOdX6r9FuKF0iMWoVCg1CZhBiMN |
TLSH | T1C501600283156F4EE82B473CE025D1244FFAFBAB5B4193069F26BA593CCC3890143E04 |
Key | Value |
---|---|
FileName | ./usr/lib64/python3.4/site-packages/sklearn/utils/__pycache__/testing.cpython-34.pyc |
FileSize | 21606 |
MD5 | 5486A26C2123D5BE3AD1483C252600ED |
SHA-1 | 00CFCEC5E436726F7CC07C525E79C1D58D5226C6 |
SHA-256 | 820B01D389CC65AE8349EE33D67D0414D164BB8E5216B500267F14D76A496AFC |
SSDEEP | 384:BoD4RGX9c3X7V30q0706z1Fk5cZLR0ZXhn8XmE7l1+nN8888Sk4:BS4RGX9c3LL0706z1Fk5Sa8XmE7l1+n+ |
TLSH | T182A2C78173430A1BF896F3F1903A42129FA5FE4B6B016346B1ECD47E2FC9756493B2A4 |
Key | Value |
---|---|
FileName | ./usr/lib64/python3.4/site-packages/sklearn/__pycache__/qda.cpython-34.pyo |
FileSize | 7748 |
MD5 | D9C5A22CB4879475475AA11A120D60A3 |
SHA-1 | 00E00D830D1AE3EED0D8850555D8A8C9E02536F9 |
SHA-256 | 8325BAFC22698AA6EDA51520B658FF6EF161956D2A828A1793368942A0E89CA2 |
SSDEEP | 192:P3aLv1Zp4CEHWj7p/4pgJaDi0QudDEQv7xv5Yn7lx2kfdEQTfopv:Q3qCQW5geJaDVQudwQvtg7SaEQcpv |
TLSH | T16EF170467F410E6FF957F2BA80B94213EAB5C09B97C0131439FFEA761FC6264812E648 |
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/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/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/lib64/python3.4/site-packages/sklearn/tests/__pycache__/test_dummy.cpython-34.pyo |
FileSize | 17415 |
MD5 | BC4A2C2B0F8668ECB6982D72699009A8 |
SHA-1 | 0215CFED636F74BDDD89D8FA5A655F8EFD2735AF |
SHA-256 | BEFB5521F6AB6628F60EC66BFF97BEF59D1B49CB5683CA46761E41E6C0AEC043 |
SSDEEP | 384:20tRt8KJQedvxi6BLaJPIw+SkWLnImoTnn5SNfReMR2JLdpcQ2WT5kNMAKazAzqW:20tRtXJx/BL4PH+SkWLImoTn5SNfcMRK |
TLSH | T19772CD9297C2895BF024F6B9E87553268EB3F5153F01BB1253F5D87D3FD0380992A28A |
Key | Value |
---|---|
FileName | ./usr/lib64/python3.4/site-packages/sklearn/linear_model/tests/test_sgd.py |
FileSize | 44051 |
MD5 | 2A30219204D8A3FDB17710890DF5C022 |
SHA-1 | 022C4A0D46C8BE6450F86A4F5A534285740DA850 |
SHA-256 | 80967239521C8F49941B2FE639AAAF0FE5F6BEBFC82FDEBF338E49F746C83D9F |
SSDEEP | 768:gqgGbCeWez6QENuvvCQw0pRHuvt1zvOHy/3M/APJYuzxja2ngbCe+DCihHF02woS:PueWe2zNunCQwIRHulV0j4Z0Ho4ECGFI |
TLSH | T17213C86501731F275347443A88BB874F6A066E334D85186DB4BD860CAF8A179B3EFDB8 |