Key | Value |
---|---|
FileName | ./usr/share/doc/tinysvm/html/svm_model.html |
FileSize | 1945 |
MD5 | FC17C4A7C36734DE65E31CDB4978DDE8 |
SHA-1 | 2D2B64FA6F1521764222BD9656DE53DF29690CBB |
SHA-256 | 4C17167672359B7CE70328A19A8D008ACC3DFD205D10DBDE5F868CBF1825E504 |
SSDEEP | 48:/ww0ZICwSwjWnWcgviZS4EZGKQggw45jGjHtItIyDGb:/X06SwjWnWcgKZSdGKQggwSjmevyb |
TLSH | T18541211FB19857DF19AA1BBC2D4790D58C5827316060CEC92C1C6B39C4A2D64686DDDE |
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 |