Key | Value |
---|---|
FileName | ./usr/share/doc/tinysvm/html/svm_model.html |
FileSize | 1922 |
MD5 | B96B468079BA5F589FA06ED5C6DFD70D |
SHA-1 | 34EF29677EBE54765F225155174EDA04FFCB4E2E |
SHA-256 | 2120FC2A2F77C274B68711EE932C7B4D849337022FEB9197D8C357E3D0C5FB5B |
SSDEEP | 48:/wG0hnICwSSRjWnWcgviZS4EZGKfggw45jGjHtItIyDGV2:/r0CSOjWnWcgKZSdGKfggwSjmevyV2 |
TLSH | T125410D1FB095A79F2AEA1BBC2D4790D58C6827322060CED92C1C6B39C862D64586D9DE |
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 |