Key | Value |
---|---|
FileName | ./usr/share/doc/tinysvm/html/svm_classify.html |
FileSize | 1384 |
MD5 | 55288251C7D1363C2643901D25B46815 |
SHA-1 | 12D3D48D6933CCCEC50FD149ACE862DE09234524 |
SHA-256 | FEBAA6330F63972284CC22A9D9014846689D07FE8396D06E4C94FD3BA9708FAC |
SSDEEP | 24:/wGJ0RUCud2eunEZCmL1ar6SFrSlD24lVeX5Pw45lVVEjHLhIZvIy9VGA2:/wCX0hnICubS1OjOtw45jGjHtItIyDG7 |
TLSH | T15221112EA199AB2F26D66FAD5C82A0D5CC28323134B08CCD39187B2C94A2478507CC9F |
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 | 28360 |
MD5 | 8F842BEAFDAE492645C0312C76558E06 |
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 | 2AF830E332FFEAD3662854B636B116792FED17D7 |
SHA-256 | FE587A8B11EC58A1DA38BD9FCBB62B975922BC2D36159ECAF886C20D6ECCA3C4 |