Result for 3C27B590821054D73A115DAF18A8D83ADA10A74E

Query result

Key Value
FileName./usr/bin/liblinear-predict
FileSize9884
MD51D1E1166C975E1ADA610D22E04C9CE22
SHA-13C27B590821054D73A115DAF18A8D83ADA10A74E
SHA-256DBEA085DA93AEADF6B90D833F1A826BA23F1BB03410F4D32A0E17E6663B595BE
SSDEEP96:Rf7xNhkrC/XBWBK6i4c5+e2Yj4gSxdPmeSyNlTrN6O8VI3OT6dz2VbR3SSj:NzhkeX8c58AjQFmeSyXrD3ZA
TLSHT17A12C689B65A5337C8D22B3E019B0A3D1776C6C9A3972F035579B1740D016AC8F2AFE3
hashlookup:parent-total1
hashlookup:trust55

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Parents (Total: 1)

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
FileSize18372
MD59AF2EE1B0FB3E0837A65E166E514866F
PackageDescriptionStandalone applications for LIBLINEAR LIBLINEAR is a library for learning linear classifiers for large scale applications. It supports Support Vector Machines (SVM) with L2 and L1 loss, logistic regression, multi class classification and also Linear Programming Machines (L1-regularized SVMs). Its computational complexity scales linearly with the number of training examples making it one of the fastest SVM solvers around. It also provides Python bindings. . This package contains the standalone applications.
PackageMaintainerChristian Kastner <debian@kvr.at>
PackageNameliblinear-tools
PackageSectionscience
PackageVersion1.8+dfsg-4
SHA-1BAA8D6DCEB91461EA5D607F62C03CCA358956A41
SHA-256EDB2E352B3E973DB44D230AA9362846B9356BCEEB2E60B818C29377411583C7C