| Key | Value |
|---|---|
| FileSize | 29650 |
| MD5 | 8ECA556658AEA6F9B0C418FAEAA611C3 |
| PackageDescription | LIBSVM header files LIBSVM, a machine-learning library, is an easy-to-use package for support vector classification, regression and one-class SVM. It supports multi-class classification, probability outputs, and parameter selection. . This package contains the development header files. |
| PackageMaintainer | Ubuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com> |
| PackageName | libsvm-dev |
| PackageSection | libdevel |
| PackageVersion | 3.12-1 |
| SHA-1 | 3192205F5514AC037A8163812374F09889B99281 |
| SHA-256 | 91B252DEA465020595B45DC26204C791395D8C4465964ED5480762F80C94F68C |
| hashlookup:children-total | 5 |
| hashlookup:trust | 50 |
The searched file hash includes 5 children files known and seen by metalookup. A sample is included below:
| Key | Value |
|---|---|
| FileName | ./usr/share/doc/libsvm-tools/FAQ.html |
| FileSize | 72186 |
| MD5 | E5006337C124562748202F0F013EADD9 |
| SHA-1 | 8F75386C43C51EBA9DA79CCDDEEF4707F856D036 |
| SHA-256 | CABBCE5987F1EB2E85E273898A3027DFA6CF97728625046553BBA1CA856C6D2B |
| SSDEEP | 768:k/9zt9pEEQrxt1gDDICgpwSFI6qGwRU9X5Bu997WOdkob1iFGTm1wVPuxM1RJcBn:K5tKxt1YF6HH5SkopiFomtxMVPXPplRS |
| TLSH | T1CE63E937DE81AE3B425362A59A0E65F87F5640FC63262A01B47C40173751F68AF3EBD8 |
| Key | Value |
|---|---|
| FileName | ./usr/include/libsvm/svm.h |
| FileSize | 3129 |
| MD5 | 55CCADEE811E639695E9BDB92582EB7B |
| SHA-1 | 5B1CC008A4953B683C6BA5D39579C3D3293D10AC |
| SHA-256 | 9B87467D3B5438C2F71169A6C684CC469CE2B5CFE54BB15F5D63A2EE7F582E25 |
| SSDEEP | 48:4gx7xD61RCpbo7SKU0c5jzx8EETxp0ZuLfUHu:4wxSYpE7hNO8JUuLfKu |
| TLSH | T18451F42CF079BC96E19E5EF2F2950C45A29961F33067DCA8CD5EE7780C8263C51F4929 |
| Key | Value |
|---|---|
| FileName | ./usr/share/doc/libsvm-dev/examples/svm-predict.c.gz |
| FileSize | 1911 |
| MD5 | FCA7F2225DDE843AE295262AB7EFAD93 |
| SHA-1 | 5C2FF374F60220E6C8BD8FAFD117FF173C9FB362 |
| SHA-256 | 5614F96FE03D0D317C09675AAEBE478065D2C1105CDB41BCC56412E57E1DBE50 |
| SSDEEP | 48:Xgx3+NdMP0CFEC8d3TALt+44jbeq/qtevMslrAreX:QxujAECg0LYSIqAMs+aX |
| TLSH | T17D412A0F17102814B789547EB93BA7D00818566CCDE1A4AA9589231DDF888FC9C8F2B1 |
| Key | Value |
|---|---|
| FileName | ./usr/share/doc/python-libsvm/copyright |
| FileSize | 1756 |
| MD5 | BA2450D038A1DCCF7AB2BDD03213022C |
| SHA-1 | 0CCC987A5165300A30521ACCCF0D0BC48F03235A |
| SHA-256 | 2C4CAF69520D90B67526C64E4C0B18B6AE1987CA0E515E41D726D212CA327154 |
| SSDEEP | 48:UGhOmi4yCNOYrYJWrYJ5zPbxmr43JD32sBEtI33tEHv:fYJxCgYrYJWrYJ5Pf3l3d9uP |
| TLSH | T15031A51717880BA329F2175171AAAEC4B0ADD03E3B239F001CB8B14D937B11ED07B552 |
| Key | Value |
|---|---|
| FileName | ./usr/share/doc/libsvm-dev/examples/svm-train.c.gz |
| FileSize | 2910 |
| MD5 | 7101B8DB2DBF0D194FB34845AC47B8DB |
| SHA-1 | 5A327061B3343DD21D3E85A30C6AE5011DE6B93B |
| SHA-256 | 6F608EDE5B18395838957BF329ACCAF127107858F91815326A2DB31292D13394 |
| SSDEEP | 48:X9swcTCYCxTd2qyje/T5ukHo+bVCgkp6Q7tnXku4iv7Q+k2RE7Lm+l03MDE+XrRj:fceEjeb5XbVCgqtMQjEvm+C3MDE+XrRj |
| TLSH | T173517DF80DE7BF2A940786A7E65C5332DAD3A92E931CC5513C85F0B18F22C9D251B236 |