| Key | Value |
|---|---|
| FileName | ./usr/bin/svm_learn |
| FileSize | 10220 |
| MD5 | FA5CADAC12D4511E0000A2C5C2AED30E |
| SHA-1 | 8C609AF7ED25E6333848EE48226A4707998F99F6 |
| SHA-256 | F1192FB75A6E17CF83DCB7151CD6A1138FF12748399C1223D9E5D9B84D3C4417 |
| SSDEEP | 96:tweO9SnAb/szKiDowXTJiCKTkux6QpdEHGmIQEtMKAAsXT2iRtGW5QZugSlga:txOJbeDowXj+5x6EiGB1i |
| TLSH | T12A22D70BBB95AC9BC4EA0B75E047538667B6CC02C79343277319C6383D4EB6E0A57B19 |
| hashlookup:parent-total | 1 |
| hashlookup:trust | 55 |
The searched file hash is included in 1 parent files which include package known and seen by metalookup. A sample is included below:
| Key | Value |
|---|---|
| FileSize | 27940 |
| MD5 | 268710102DA484C90FEDC79863F2821A |
| PackageDescription | SVM trainer and classifier toolkit SVMs (Support Vector Machines) are supervised learning models with associated learning algorithms, and have been proven suitable for a large number of real-world applications, such as text categorization, hand-written character recognition, and image classification. TinySVM is an implementation specialising in pattern recognition. . This package provides tools for developing SVMs with TinySVM. |
| PackageMaintainer | Giulio Paci <giuliopaci@gmail.com> |
| PackageName | tinysvm |
| PackageSection | science |
| PackageVersion | 0.09+dfsg-2 |
| SHA-1 | F83D90AC68AF2D69F985FB7E6564763C97ECB2D1 |
| SHA-256 | 57E418AD95BE87680A1EC81A96DF89F9B64B39817FF67308B18EEB3B09554BD1 |