Key | Value |
---|---|
FileName | ./usr/share/doc/tinysvm/html/svm_model.html |
FileSize | 1941 |
MD5 | F051B0E19EA63A90F87B624B83B5BE97 |
SHA-1 | 17808B9C5769EB4D0745F2FBAE1AFDC2FAC7A4B2 |
SHA-256 | DBEC45C8D7CC792FF193AF6344D5B87D18BFE5B31D8F75630082B3B2A41A6B02 |
SSDEEP | 48:/ww0JNICwSwjWnWcgviZS4EZGKQggw45jGjHtItIyDGm:/X0JOSwjWnWcgKZSdGKQggwSjmevym |
TLSH | T15441231FB198A7DF19AA1FFC2C8790D58C5817326060CFC92C1C2B39C8B2D64586D9DE |
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 |