Key | Value |
---|---|
FileName | ./usr/share/doc/tinysvm/html/svm_learn.html |
FileSize | 3761 |
MD5 | B3588E012EBA0FDEBF1740FE90A8D7D9 |
SHA-1 | 111AFAC23D318407B7B668FF523FF52362332F03 |
SHA-256 | 5A14F63CE4D3994B9DB0302D79D2854BC90B9D5186B51989294E12972B29CE0A |
SSDEEP | 96:/z0CCQjtkSsfZSUIeSCQ0rCbtprM+0jJ3j80pYaWL08wI2z98twSjmeyyV2:/zdxefZI3CnCnwxVT80YHLFwI2z98tw/ |
TLSH | T10371201F70956BDF2AA20AEC4C1660848E2C0A767510FCCD19CE2F39C476CB5A52DDCE |
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 | 27980 |
MD5 | 97CB1BA1F4C7807F81D4FA5AB4C3A2E2 |
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 | 922559E680CB271D12E4D1D86FF20E374FBA94F3 |
SHA-256 | 03352685C4EC39DD3378E57CA779708866EDE76105847BF0D55790435D20F527 |