Key | Value |
---|---|
FileName | ./usr/share/man/man1/svm_learn.1.gz |
FileSize | 1114 |
MD5 | ECCEA581FEBB62720593C62282D8386F |
SHA-1 | 5C58BAD7C0F1ED2A7D37FC083B9B06D0F40F8547 |
SHA-256 | 1EC8D71173741FAB588DC19573E0FCCB6FFBC90B48A5ED1F66FF22E71E182F4B |
SSDEEP | 24:XnycYDI6yJk9t9/996GK7BVbpipCohPdsooawbRgfq:XnycYDI6m0tj471ipV9dfra6fq |
TLSH | T14721F99A36FD7E2EA83ADEB623B0111E2D0E5202537843222695330A2647C3774671C8 |
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 | 25106 |
MD5 | FFF2FF64791D0E1D6DDC288831CE3A44 |
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 | 7AECB645AB3DC74E2C84A6683205A4463E14D2D3 |
SHA-256 | 0BE6915D52EF4A1D93ED25AAE7FFD670D0CD34F0186EA5CD66F459B54FB57A15 |