| Key | Value |
|---|---|
| FileName | ./usr/bin/svm_learn |
| FileSize | 14568 |
| MD5 | D83EFAA65371028A67427078BC4AEE33 |
| SHA-1 | 23DE2122704C059BD8D8CF4C3887279C8093033A |
| SHA-256 | D0C8336A752B6190C91E1A04F0E25F8A755A4599284C1DAA8C15A34090649440 |
| SSDEEP | 96:9lKXBWBaDVK/0ljvAoQAgq9lT9VR37MgTbFfmfuJcRXtcqwAu5wNJS6IWnRX2M:9lKX8SKcpYAP5r7Mg3FOf7xz6wNJS |
| TLSH | T1B9627303B76A9E5FCA982136C95F0A7073716D4A136323039214A3762F8AF6D8D7C85A |
| 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 |