| Key | Value |
|---|---|
| FileSize | 104452 |
| MD5 | FFDD7A0F13052F3F839AF17CFBF732FB |
| PackageDescription | LIBSVM binary tools LIBSVM 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. LIBSVM homepage: http://www.csie.ntu.edu.tw/~cjlin/libsvm |
| PackageMaintainer | Chen-Tse Tsai <ctse.tsai@gmail.com> |
| PackageName | libsvm-tools |
| PackageSection | devel |
| PackageVersion | 3.12-1 |
| SHA-1 | 9FA1639167DDB7973D8D25F9EACA82203FDACF27 |
| SHA-256 | 1BF814DD45B49EDD26E2AE9926B178B7A6C6C130D48C616B8E9593F4A15CA2D8 |
| hashlookup:children-total | 19 |
| hashlookup:trust | 50 |
The searched file hash includes 19 children files known and seen by metalookup. A sample is included below:
| Key | Value |
|---|---|
| FileName | ./usr/bin/svm-checkdata |
| FileSize | 2479 |
| MD5 | 3DE5CE671F573AD56F56537D54D06E28 |
| SHA-1 | 02548E7ACFB6F8190BC8ED11C1B4212B456BE95D |
| SHA-256 | 3E7A4EF93EFB3692361E2DE98F2AD59FFF097914ED62BB6F42ED0567E6AC7CDD |
| SSDEEP | 48:7EaDpfG23vnypeB+hnb04ZVONUTSuaCDeLqTFat8K1UAUXC1MBpku:7EatRjF4ZV0U3iLN8K5Wku |
| TLSH | T16851E54FD51E418EAA2000BEA7A8040E692D40B750B0622BF9DF1671F7C0DA3B8BC75C |
| Key | Value |
|---|---|
| FileName | ./usr/share/man/man1/svm-easy.1.gz |
| FileSize | 443 |
| MD5 | 281FE6BE43E09EDE79079A0A41822D45 |
| SHA-1 | 08448AAFA41A8D0B614FC270CAEADAE1ABDEE687 |
| SHA-256 | 4F27BF8B8DDD1AEDEF1941564619144C31300303057D7E16EA0B95CFEBB4D38A |
| SSDEEP | 12:Xbaq+iBDP7uEbv6/7bbzSgsKoBGQLzeJ8lwuiOYXr8M:XbaqjuE76jbXSgieJKiBwM |
| TLSH | T12FF02319D59BE07B4B601A26C244514E104E712D239B54DC044C8B623F16305052B136 |
| Key | Value |
|---|---|
| FileName | ./usr/share/man/man1/svm-grid.1.gz |
| FileSize | 605 |
| MD5 | B0D05E1B74CCE1916C662B11EDBE76B9 |
| SHA-1 | 0B4F745B1A61B3ADB4B461DB957927EF7EFF4AB4 |
| SHA-256 | 2CB38D3311D02B7F93047BF3EB0E6DA416412D1579E227D5AC1BD0C3CBC0FCEE |
| SSDEEP | 12:XemT9OlLY1f2AyEM7ie7LI/D3/OfyS5LYM9R8Q+5hJvtbzQ/:XeU98Lq2X3WT/O669gNVzQ |
| TLSH | T1D3F0026114CE61EA8072C066D78D5E189A085AD1AB49E74A8B0C44961B7E12E3799E0C |
| 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/man/man1/svm-predict.1.gz |
| FileSize | 1289 |
| MD5 | F00CCCE7F82CD612CA1FC4E86BA1A8E9 |
| SHA-1 | 14990211C766E499D1FFA23E74AC485481AF8F3C |
| SHA-256 | 3BC48CD236DE19733413609F92B07CAD04A5079B53B08BF301866E0E8DD2D50A |
| SSDEEP | 24:XZOj29kkriyUaOQJRkQ6BCAl5BCuVm1B/LSxWLHvpD2zsdiSF/+MQQl:XZO+EAOsaQ6BCAl5BCIYBPjvpH/+MT |
| TLSH | T1882117A9E7202D074F690B75A1E124A0E6EB01D50F65ED4448438BFDFA3DC23C0CE8A0 |
| Key | Value |
|---|---|
| FileName | ./usr/share/man/man1/svm-train.1.gz |
| FileSize | 1715 |
| MD5 | 6C642B9748BFA2BEDFF471F3EB616A8B |
| SHA-1 | 246BDB220FC495E0A3BA39FA7E5C17455538E9FA |
| SHA-256 | F88978DD8D0E9BCF50BDB391F16DDBDEB31FE96031A88164F1D00C1857C14805 |
| SSDEEP | 48:XPVwHmdlOQBSVe5AKLfiDFgP2L+7q4+dZWUlxr9xMuC:9wHwlOQUBDFa2LdlTMV |
| TLSH | T103313DAC6F589411C53022587CE36EF1EF88C1A4171CA53D6EDF40A9584568B936F24E |
| Key | Value |
|---|---|
| FileName | ./usr/share/man/man1/svm-checkdata.1.gz |
| FileSize | 486 |
| MD5 | 505F5FBFFA0787502600B6E39198636A |
| SHA-1 | 3601DBCA34991A2B6FAF4AFB93B6889ACF33F766 |
| SHA-256 | 243D4BD26DFE8B3ED4DA2DCA53A40B5417FBABA4947F5B323709F133D1CDA757 |
| SSDEEP | 12:XggAE2gsOqH++2ETtARZHjwntaaoA+MZoL7Jvi3wkiEa/:XlAasTe+2AKsnE6+iofJvigkiz/ |
| TLSH | T1BEF0C46A0E616408C8A582B88472DEF5186C3829827A0C4F8D06134687F17E0EAE3E22 |
| Key | Value |
|---|---|
| FileName | ./usr/bin/svm-grid |
| FileSize | 12117 |
| MD5 | 35D03E58C201D4B26AD34430DC4E1245 |
| SHA-1 | 370B6578F9D2E2119F8E25C54330DF95F7BC0C47 |
| SHA-256 | 6634191CF0006FED5C218FC30EE3136268F679172A0B6FF46FEEF37115CCE82F |
| SSDEEP | 192:tQ7HFlh2bYo45MjhIFVtc35VZqFhbezKIqXqocfUKxAZv+vfvfMHBQHWvJ6KGHVS:t032bYdSai5PYSKIEqvfvxAInMK2vUK/ |
| TLSH | T16242A51E453B4A90E30395BE08ABC219368D7C13B1489534B6DCCB580FA747FF2A5DAC |
| Key | Value |
|---|---|
| FileName | ./usr/bin/svm-train |
| FileSize | 37684 |
| MD5 | 69B26E9A4F378EE6C92B777E6FF2302F |
| SHA-1 | 39E2DA2606E448F5C94C6DD0A5B685DE7A2F71AA |
| SHA-256 | FE51D48DCD9C5A22969791281F5B9C1420BDE8447FDB1E1D34E15C458D005F68 |
| SSDEEP | 768:pJQALoJuNfZ/GWIAXGpl+I4vfYCb9fs1NRGmweRNa0hy6:vQAp/GlTpl2vQCb9ccmweRv |
| TLSH | T182038EC5D1525823C64576BFDB575B40A3F4D8CCA23B4F6731C88BA568D39378F22AA0 |
| Key | Value |
|---|---|
| FileName | ./usr/bin/svm-predict |
| FileSize | 35644 |
| MD5 | 84ACA1C06428DC7DB38608527E308583 |
| SHA-1 | 4B36DD6343CCCB41ED64A3B79FFC7967C661A0D1 |
| SHA-256 | B8892469FB6AFEE08D1EAA412EC07F7516558AAFD306B00D784696FDE2DF4A73 |
| SSDEEP | 768:SQALoTuazrI7gO+2C3wH+VQcLM1vBNRQZNcj3A6:SQAEI7d5C3wshqGZN |
| TLSH | T1B1F2AEC5C2526823C5CDA27AD7678A8436B4C8CCA2374F6731D893B51857EB58E367E0 |