Key | Value |
---|---|
FileName | ./usr/share/doc/tinysvm/html/svm_learn.html |
FileSize | 3803 |
MD5 | 29600442A03177A98044B9EAF786584A |
SHA-1 | 8ADA79EB7A0B0A7D49A456D045D9DB6C34ED2EE3 |
SHA-256 | F9672B59DFCD890E0DD6C4A7D2CDD9C02E06567CAFC5BAD47B7DF889DDC12655 |
SSDEEP | 96:/v0VCwjtJSOZ7UILSCz0rCItpYM90wJmj8XpY3WLX8wIpz98twSjmeyyIr:/vgx9Z1WC0Cy1+iE85YGLswIpz98twmO |
TLSH | T1B371321B7295ABCF16A60AAC8C5660804F3C07767610FCC82DCE2F39C4A6C75622DDCE |
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 | 24854 |
MD5 | 53F837944AFF716E7773406EC3AA8E51 |
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 | D6EC1ABAC3F6C0E450F9CF455C766DB238AE78DF |
SHA-256 | 3B52D003B96724DECCA76F046781CDED76EF5EFB5CD7907DDB028E5E57E772C1 |