Key | Value |
---|---|
MD5 | 8EC64F622C324DF5A601DEC5D9508102 |
PackageArch | i586 |
PackageDescription | sklearn is a Python 3 pypi_name that integrates classic machine learning algorithms with the tightly-knit world of scientific Python packages (numpy, scipy, matplotlib). |
PackageMaintainer | guillomovitch <guillomovitch> |
PackageName | python3-scikit-learn |
PackageRelease | 2.mga9 |
PackageVersion | 1.1.2 |
SHA-1 | 390CD04FD06C3A3F2996973B7511D1FA632EB787 |
SHA-256 | 715E352839A0FBAFB763A9F5F3408FDC9FB7C9870B453A68A3A14BCE7447F29E |
hashlookup:children-total | 1813 |
hashlookup:trust | 50 |
The searched file hash includes 1813 children files known and seen by metalookup. A sample is included below:
Key | Value |
---|---|
FileName | ./usr/share/doc/python3-scikit-learn/examples/decomposition/plot_beta_divergence.py |
FileSize | 758 |
MD5 | C1CA235747221CCFED0F8A6EA94357F4 |
SHA-1 | 0023E169B3A095DA90B8ABC08C3C22C7C68A3E47 |
SHA-256 | 0320158F2E392642F96A9AAE9CEEF046457E7CEA763EBB9DD4E7724CF023A338 |
SSDEEP | 12:zOHAC9N4OHk3hVweeJZmTyDDjUAakzpWA/wmh/jGd9opGCdEC8OG0AL0w:OAC5k33we+mTy3Ta0gA/9goFdECnul |
TLSH | T12001F4433E4B1702C75FC0D82CA4DC810BB052243D88622932EFAD41DF06B8C91138B5 |
Key | Value |
---|---|
FileName | ./usr/lib/python3.10/site-packages/sklearn/neighbors/__pycache__/_regression.cpython-310.pyc |
FileSize | 16454 |
MD5 | F46A30637F7186972F01B724F6273C57 |
SHA-1 | 003675906EF9F07E14A8EFC39F82580A524B1653 |
SHA-256 | 7C796D8DB93C05926CEE9CDE9703D1BE5673F49301B9773D36B7105C8CCA4812 |
SSDEEP | 384:hPpPa09SQH7Fqa6ClbxQWbicmPa09SQc7FHDYoMxlob:hPAGSQbFqa6CZKWbi2GSQ4FHDYzLob |
TLSH | T1A672B5313E402733FC93EAB3A8D95246CFA0CD27A37B641434ED66981F4A85427BD68D |
Key | Value |
---|---|
FileName | ./usr/lib/python3.10/site-packages/sklearn/utils/__pycache__/graph.cpython-310.pyc |
FileSize | 6651 |
MD5 | 291CEEC55964D886D6CAAFD97CA023A1 |
SHA-1 | 003ECE1D7E07C3AA27A8876315EF1E715817BDA1 |
SHA-256 | 5A61CAAAF336C3822503DE66D66E4289A9B93B79C45D154855A618E48D4643D2 |
SSDEEP | 192:Jv5CMkOejaCMHdaza/glbdvJZcLnI2RdUWVzN3Chw7:J6O3CMHdazNlbNJZ92RdUWVB3Chw7 |
TLSH | T11DD1D83A0A8E0235D2D2D0F39EA62E83DB51C8979717614C75DD423C1F629A5C2BA7EC |
Key | Value |
---|---|
FileName | ./usr/lib/python3.10/site-packages/sklearn/linear_model/tests/__pycache__/test_huber.cpython-310.opt-1.pyc |
FileSize | 5430 |
MD5 | E8EBF51FF962957354638C692FE7DF6A |
SHA-1 | 0064F961B2B50DCE457F5F6EA6B80D6FD106274C |
SHA-256 | D9C1EFF57EBB69A3CB03BA090F8CB6618C6B8E0CABCCD333C48D74835D149D9A |
SSDEEP | 96:EHFPXtig/X55SX+TXo9VbuVkXXXaEXhU/vZXCiMGf5XjykXJEYXoN+0DXghul0XV:aVig/3SSYLuVknqERk0o5td44Cwhul0l |
TLSH | T141B1A6C0984B5E1DFCB8F2F8701A06195AA0EB6A87CFB90D4898A19D0ED65C72D77970 |
Key | Value |
---|---|
FileName | ./usr/lib/python3.10/site-packages/sklearn/feature_selection/__pycache__/_rfe.cpython-310.pyc |
FileSize | 24074 |
MD5 | F5624E474163423CA7A42D781299DCB8 |
SHA-1 | 006CACACB6225B015D567BDC75C46CF8A22B818D |
SHA-256 | 57A2629CC8C56B8AD97B937418CC31C60AF7E3EB6B4C054783F5C4A85C20DAFC |
SSDEEP | 384:NPXz5iXIm+cz0TttttR+pq5k+L5fLP0Zq5i4/8x9mhjxglttttOOYShGPHKgEi:RCw55k+L5reqE2CVGH11 |
TLSH | T12BB2C54E6D020B3BFE53F2B755E80052EF6149BF83C1105578AE92293F859A45BBD2CE |
Key | Value |
---|---|
FileName | snap-hashlookup-import/lib/python3.8/site-packages/sklearn/utils/tests/test_optimize.py |
FileSize | 769 |
MD5 | B80690351B758C0AC49FF9179F928FF2 |
SHA-1 | 009471A6046B0397C011D2E2A4B3ADC7D488A9A7 |
SHA-256 | A1D9AC8388E1953066FFD609B370FE5C1329FAFC6297C2DAF3F75D32B9EE865A |
SHA-512 | 8DC7259BCD3E1AFDAFEAB574FFC656FEF7322E3CF3E7099C21E885A52122AB0E13C08CDF799F1BF5D4F920AE71F509CAD91B4D6C65445669AD49BB221840578A |
SSDEEP | 12:rOTyP8xOz68oOyqBuegsClUVs/MaFFR3rcsNt4nrsDapt6d+je5sLbQTd040uNEv:rOTyxPyNeYWsv5krs8tiuefTe40umv |
TLSH | T1960197B32BEB6390833792660C1FE425D369E963591018FCB1AD0FC23FC4169B6E12C2 |
insert-timestamp | 1728267455.0952032 |
mimetype | text/x-python |
source | snap:43LOJ1RcqawGIwV10Xk4HzV76JkxgFo2_383 |
tar:gname | root |
tar:uname | root |
Key | Value |
---|---|
FileName | ./usr/lib/python3.10/site-packages/sklearn/utils/tests/__pycache__/test_random.cpython-310.opt-1.pyc |
FileSize | 4223 |
MD5 | 35C6BDEA9D35E52F95426BD485378B1A |
SHA-1 | 00AF8059B836E96EF164EE5C2422823C87B60D66 |
SHA-256 | DFE7865FBEC86C85F29E3F9A684FAA9EC9DA86DAD4ECB4194359EEA7FF242D73 |
SSDEEP | 96:tH8NxqLQagRrkapVvPxZHysHVmtdcRHbmslouI3X:tc6QagRr5hZpVUhslG |
TLSH | T1F5918283E8029A9AFEF5F13D81BE9329524EE3447F8AF58B4E00F10F5D692C02460184 |
Key | Value |
---|---|
FileName | snap-hashlookup-import/lib/python3.8/site-packages/sklearn/linear_model/tests/test_logistic.py |
FileSize | 71530 |
MD5 | C67AD0D16050812F9411B6BBE7F454EA |
SHA-1 | 00BA02FB4DE29580AD5E03BEA1F1102EF9DAC675 |
SHA-256 | C9DE19D248B3F33FD8BE43C5C7F5A9CB16B7C1D3894B2A7E53D05A4C2F42CFA0 |
SHA-512 | F35D8AF02149B3140970E2FC872CE8BB15E336C2AA13E91D1D39C8D45EAEECBA6858C2D9B25665EB772E0E1FA6D00F75D9DAF02F012811CFD0B278D504FF9F87 |
SSDEEP | 1536:wB2Pmle+7Q/WDBzBZXu1RBnTRhgzgPALXh2KPgtLFh+bONKB76LZdcvj:wUPmlDQuDlBZeHBnTy2KPgtxh+b1B768 |
TLSH | T1346376025825293F63C3813D48FA515933566E1B9D41643BFDEF99042FCF8AE7272AB8 |
insert-timestamp | 1727043686.6000097 |
mimetype | text/x-python |
source | snap:qlekdqRb9ScClFkFW13cMQrTnfuSU59E_41 |
Key | Value |
---|---|
FileName | ./usr/share/doc/python3-scikit-learn/examples/cluster/plot_optics.py |
FileSize | 3572 |
MD5 | AD28E250171348F2AAF99F1133492165 |
SHA-1 | 00C09800C1D4CC8B6F3C37A65DABBB0CAC07F78A |
SHA-256 | 96DAACAF01C3A13CCB8B523E8768889B077FD3728A51E918ADE468B5B6C8DAC1 |
SSDEEP | 96:1L2Fr9mFJsmPb7t1Gwf97o5Lh3yV0ZPnPsZPSrwIZP4Br:ZGr4ymPbR1Gwf97odh3+0hsIrwI2Br |
TLSH | T16071F0282A451223EF96E0679CF1A9FD23C1913B9B004BD97D3D0DD42B0E379F6A1D91 |
Key | Value |
---|---|
FileName | ./usr/lib/python3.10/site-packages/sklearn/utils/tests/__pycache__/test_weight_vector.cpython-310.pyc |
FileSize | 783 |
MD5 | C9825870467A509D840FDE7DF436EB80 |
SHA-1 | 00DD389418AF8616E7873E17196ABB1C19601E84 |
SHA-256 | F7DEAFF71A0503996DB92D934E89F04A081E171F2B12206F0D982D3AC010AC27 |
SSDEEP | 24:igL24MZrZgt04//FYammzMgDqKEwxQA/+vKP5n:vSjtSZhMejEwx5n |
TLSH | T1C50120604A43782CF553AEB35554512636D0C5DAD100C4912E58263F3E5C3222B13B13 |