Key | Value |
---|---|
FileName | ./usr/share/man/man1/svm_learn.1.gz |
FileSize | 1114 |
MD5 | 287F50855AFC42F81DBC518F500C5132 |
SHA-1 | 16CA14A9DDEC59D4714C45F57362651B0AF5EA57 |
SHA-256 | 1CB4794301AC80BEB7DBCE5D1A95F0E93F0D211DA8791B45EDE764E37740A4D8 |
SSDEEP | 24:Xnycvx95bk0RzzHtPQhfhg8NXy44zxpUCk3uFuoMJ9:Xnyc/dlEvNi4WUCk3aGJ9 |
TLSH | T1E021F98680C2F9EEB0F7663B0035F2C4292905E0CAB83D2805D629AC18239CA5263C2D |
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 | 24886 |
MD5 | 10CA665CD47B175E97B93A7DF99B7213 |
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 | 8E7372C40351033EB34F595BB8ED4F8A20E2F4B8 |
SHA-256 | B5B6F03EBE90753FF1E26DD9FA6EAB644ACD7EEE755CFC2D3B0D9DFFFECC8931 |