Result for 0AFE65E640ED14BEF1C2C65391E9715EDA428C1F

Query result

Key Value
FileName./usr/bin/weka
FileSize327
MD5B164D772F536CAECDB18D028305F704C
SHA-10AFE65E640ED14BEF1C2C65391E9715EDA428C1F
SHA-256A3980CBEEA56E30508D7B6B7C76E95F99B765D30DEE6BCFDFE033A7FE176CBE2
SSDEEP6:WoaIcCvexzAt2WARAzAY2i6WARAzA96rARAzA6ASzAOQZ6zATGFjKVQcbtYc5tiT:NcCvkzaGRAzX2iiRAzqDRAz9zTzPjKVk
TLSHT1BDE08CD471101328E4BF8670FF8204983480A0ECCB8DECAA90E1208E6F6156204E9B22
hashlookup:parent-total3
hashlookup:trust65

Network graph view

Parents (Total: 3)

The searched file hash is included in 3 parent files which include package known and seen by metalookup. A sample is included below:

Key Value
MD5B0B8078CF91886F15A4FD2A864DDF6D0
PackageArchnoarch
PackageDescriptionWeka is a collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a dataset or called from your own Java code. Weka contains tools for data pre-processing, classification, regression, clustering, association rules, and visualization. It is also well-suited for developing new machine learning schemes.
PackageMaintainerFedora Project
PackageNameweka
PackageRelease6.fc17
PackageVersion3.6.2
SHA-1945084EDECE549D5B2BC9905FACC0696B3ADB996
SHA-256087F40D6561091568F86907F113C66AEA8FB6D63C1FDAFCFC6F96064AE11F95F
Key Value
MD54E2BDC224F3433875E1FF532F0DA5B64
PackageArchnoarch
PackageDescriptionWeka is a collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a dataset or called from your own Java code. Weka contains tools for data pre-processing, classification, regression, clustering, association rules, and visualization. It is also well-suited for developing new machine learning schemes.
PackageMaintainerFedora Project
PackageNameweka
PackageRelease6.fc17
PackageVersion3.6.2
SHA-1631940E30BD74D2B59E3A9B74AAABB795A896805
SHA-256CC13AC6831C8F5B22471187D55529EBDDD2A56CD465BBBA070FA9EB0EB7FA0F1
Key Value
MD56CC4BB080A104D66E2BD639683C06D63
PackageArchnoarch
PackageDescriptionWeka is a collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a dataset or called from your own Java code. Weka contains tools for data pre-processing, classification, regression, clustering, association rules, and visualization. It is also well-suited for developing new machine learning schemes.
PackageMaintainerFedora Project
PackageNameweka
PackageRelease6.fc17
PackageVersion3.6.2
SHA-11E29FADF4F5D8F231B0A3A4B67F1025E40B3D15B
SHA-2562904DDA4EF487E5F2E7BCA470D978EAE0E90DEA812ADE60D3BB368A43EC0BCDC