Result for 80627364A75196652AB8EACCE6304D7351333865

Query result

Key Value
FileName./usr/bin/liblinear-predict
FileSize10576
MD54CD873B34E1C41B2F3B57FA475886C2B
SHA-180627364A75196652AB8EACCE6304D7351333865
SHA-25674059AC9376A5AC9B30AB544643E1F05878F7C53617DAF67895F65097E92E207
SSDEEP192:GcKRX3X8clE6QN65Q4ttpKVy3XGLFUHL90SyM:WXXe6QN34tWVAX1F
TLSHT12022A607D1A28A3BCC94413686AF86343773ED78DB71432B1984B6701942B9A0F5F7E5
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
FileSize19088
MD5998CF1A30AB021D9FA501CE29D3AAD64
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-1792BD63655EABAA8E3F209D86398BA3318334DB4
SHA-256A12C07C8C6973093128D62173DF3E15042CBACC2082199763CEE1312F43E6CF7