Key | Value |
---|---|
MD5 | E792E5D6D39E3A15CC843693E91BC76B |
PackageArch | armv7hl |
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 | 2.fc32 |
PackageVersion | 0.22.1 |
SHA-1 | F83CFCCAD333126AEBC7CBD1D680322CFF6C40CA |
SHA-256 | A9ADCAC6402F3242E6803C3B3D5446413A23AE4D573920779B720BB312C7437E |
hashlookup:children-total | 1836 |
hashlookup:trust | 50 |
The searched file hash includes 1836 children files known and seen by metalookup. A sample is included below:
Key | Value |
---|---|
FileName | ./usr/share/doc/python-sklearn-doc/examples/svm/plot_svm_margin.py |
FileSize | 2540 |
MD5 | 20F0800268AA3B127A61866BEB151FF0 |
SHA-1 | 001C2B7EF85E6BFACF735090F2C5E656263B182A |
SHA-256 | 800978E1EF0A17DAE6DEA3ECAB717245DEA9CDBA8F649D4E4A2877352DB3E680 |
SSDEEP | 48:CdEGkJVbTOXwNUh6EPXu6HSghmkhslNMftKVGbioWGF:CvQcX186HIkh6Sms |
TLSH | T140517401364C73B09B4381983DE7ADB57761A17F5D80282FB1AD6244CF18BAAD739D8A |
Key | Value |
---|---|
FileName | ./usr/lib/python3.8/site-packages/sklearn/preprocessing/__pycache__/data.cpython-38.pyc |
FileSize | 627 |
MD5 | AD97C69E70B848D148B668B3EBC19A25 |
SHA-1 | 004710C639FABF36C8BD53E85B9236AC9CABE1CB |
SHA-256 | F1420A1C969CA084DDBC61817FAD34FC66D74616597F3375FCAE3051763B7C46 |
SSDEEP | 12:cCaK2ZILsS/YJ5lZpP6PhnHA20SKTwDWeyroqQBlk6MRcsc3VDn:cC8Wst3ZpP6Phnw5TwDWea0a6Aqh |
TLSH | T1A1F00CA2274D2B32EEA1B2F920110A2147F00E7263088203BF28CD0F7A862C50108B6E |
Key | Value |
---|---|
FileName | ./usr/share/doc/python-sklearn-doc/examples/applications/plot_species_distribution_modeling.py |
FileSize | 7970 |
MD5 | 46FB3C87E92A0D145492F244860459FD |
SHA-1 | 005689838EAB53866B9804164514E5CC80C8E08D |
SHA-256 | A34FA8826C4DE8FA6B695DC1AE85FA4F4EE0B4D12062B4CEF9EF213479E14DD9 |
SSDEEP | 192:ooYmsjw0Kq7Ib808OR2eo+1MWKI1SPPcTzcHF6eVIQ2:4nxh02eo+1tSPMz66eVIQ2 |
TLSH | T1DFF10A27BB453769B74380ACAF9D14C3B737891F99903468B76C80802F1D338EA3EA55 |
Key | Value |
---|---|
FileName | ./usr/lib64/python3.6/site-packages/sklearn/utils/__init__.py |
FileSize | 40467 |
MD5 | 915ADC15DFE20A236464623D7A80C080 |
SHA-1 | 007A977776B5CB521A64A5039647BCC0C2604356 |
SHA-256 | 3495791DB34C1FA6B4DD5F1BE1866BCC84E3D1740E4BC6B9C1F5F64DD69D529F |
SSDEEP | 768:wJcWQqBqmcDA7AIhgDTGHeBvdaDn8or3Mb49Ad55pb3PbzNB:fk7AIhgfGH8vdaDn8ow8Od55pTb |
TLSH | T14503D413AD451A3E4A93D4F22CDE8412D725A43B878458383CED96383F5693693FE3AD |
tar:gname | rbarak |
tar:uname | rbarak |
Key | Value |
---|---|
FileName | ./usr/lib/python3/dist-packages/sklearn/metrics/_scorer.py |
FileSize | 29414 |
MD5 | 45D67D6CCFAF7D02DBED36011AE86551 |
SHA-1 | 00E9E496C7C5B64D08DA721F5B6E282C25215F29 |
SHA-256 | 9110309212C69C5D7B056F20A4D2058409AD03C161CDD030EE1BE0A1C54BC524 |
SSDEEP | 384:Buj9Gx+yWwoNUwOX6iV0fbN66k3BYQExv5dAaoTbWP:BWGx+yWBGv7cc/3BYQHav |
TLSH | T1ECD2A529FD1B75218B27D8BDB8DBD016A304997B4A502864FCCDC62C1F0595E83FAADC |
tar:gname | rbarak |
tar:uname | rbarak |
Key | Value |
---|---|
FileName | ./usr/lib/python3/dist-packages/sklearn/manifold/_locally_linear.py |
FileSize | 27236 |
MD5 | 53F844D44F5EBC8B13D1E55A0A45560D |
SHA-1 | 01147E9758A791E79561896ED60D3B61A7FF5DF4 |
SHA-256 | 1D20B837321B00B823FCF32BFA5AC2AE31A3BC6BA950B172BC638BC95565CD5F |
SSDEEP | 768:WKhBnzDy9c/idd8hZHg+8y3B2zK2TBjo5DA+pchNzvyco+AzG6XfB2CE:WKhBnzDy9cqKMa6jmcjyzZvMCE |
TLSH | T187C208323E41753AFA87C16388E9690FDB98DB13D9855C323AAD46282F0357523FDAC5 |
tar:gname | rbarak |
tar:uname | rbarak |
Key | Value |
---|---|
FileName | ./usr/lib/python3.8/site-packages/sklearn/inspection/__pycache__/_permutation_importance.cpython-38.pyc |
FileSize | 4352 |
MD5 | 28B57DC3EA37E7DBBADB9B81DEFB08F4 |
SHA-1 | 011E38D0CB3FFB5BFEB82657BC633E6AAB6C6755 |
SHA-256 | F4200E9A8C20D3D911595F42D07959FC38EB8F03D7EDFCEC547D706CAF8F713E |
SSDEEP | 96:aY9ivQHfL4BwZBAIRBhB5S/GnjN8B/lbVdpxVnidIC4ecF0t:aUHEiBAI/h6WOddZntC4dm |
TLSH | T1F3917542BF019226FE53E37261AD402BCB73605F774558217E8DB9253F44092A7DEB4D |
Key | Value |
---|---|
FileName | ./usr/lib/python3.8/site-packages/sklearn/ensemble/tests/__pycache__/__init__.cpython-38.pyc |
FileSize | 158 |
MD5 | 70C8391A0472F99F769EA8BB96D1BA83 |
SHA-1 | 0127610D09A7750648602478CEF559BA44727895 |
SHA-256 | 3832C4ADC831790C70A6B229C91C5639CE6D192AFE30BAA8A01C5D2CF9BC2167 |
SSDEEP | 3:UtRe/c/luleh/wZWemKDXKE9YAKWMmoWrz4Az+iA6BRkcTit:cJqeh/wRaE9YvLorkAyiAcD6 |
TLSH | T11EC08C00854A8392F52DB97E2810431460C0CCB0F1CE42822D48A1892C046000D51C01 |
Key | Value |
---|---|
FileName | ./usr/lib/python3.8/site-packages/sklearn/cluster/__pycache__/_optics.cpython-38.pyc |
FileSize | 29462 |
MD5 | 1BDA84AAB640F120114A5EA45F49F49C |
SHA-1 | 0147E45E8AF14AF393A80E16CB94D8481F7F7FDF |
SHA-256 | A9A2312DF54E7D50BA53445A8BBAF6460963BFBC4FF61D54DFEEF5D22013294A |
SSDEEP | 384:DW7tratQqmtQ+xuEFxihJ0LPvKmdxSSh/YR/etexGx7K5MAeUZ28dzJ8Ntu9agvd:DWoSxiIL5aiKjZ21OD1Km |
TLSH | T170D2D8367D00233BEF52F1B7989D45EAC241542BE2A5A0A538DD42581F075ACB7FE78C |
Key | Value |
---|---|
FileName | ./usr/lib/python3.8/site-packages/sklearn/ensemble/__pycache__/_gb.cpython-38.pyc |
FileSize | 83340 |
MD5 | 94C5CCFBB17780182FD8871914DD477D |
SHA-1 | 01916EAEF1EEC44359D54CC6329FC12F58EC2648 |
SHA-256 | DC540A7253E6206ABB8EBCA0FE6DAD70C74302DAC5DEC583E440A441B05F6C93 |
SSDEEP | 1536:pFF91s6M8QgXBy2JZzWVShBPC56AL1DMbCYIA2U2sgFKuZ:LOs8fCG5 |
TLSH | T13683FA2E7D022B7AFE23F0B294ED024ADB25457F93C25111B4AD96192F1246C5BBF39C |