| Key | Value |
|---|---|
| FileName | ./usr/bin/svm_model |
| FileSize | 10720 |
| MD5 | FFAC8A71EFD965FC26C513FEEB010E70 |
| SHA-1 | 4260810C322A2FED2491B6DA2E7844C9DCEF67A3 |
| SHA-256 | ECA6FB1F1EE6319E4C37A34AD2F048290B7DE4EF3893AB88EAB3FC81788B7985 |
| SSDEEP | 96:qr7N8m8gXBWBauAiqwaSBx+baRENx3Qw+HLHneVzVgKZfMWSlxIvQ7yQI:6h8RgX82twQuwKD8zLf1SDI5 |
| TLSH | T13722610EEB48EE2FC8888376599B07B17331D649D3564367B80CE274AF8378E1E64685 |
| 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 | 24854 |
| MD5 | 53F837944AFF716E7773406EC3AA8E51 |
| 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 | D6EC1ABAC3F6C0E450F9CF455C766DB238AE78DF |
| SHA-256 | 3B52D003B96724DECCA76F046781CDED76EF5EFB5CD7907DDB028E5E57E772C1 |