Result for 1FA781AD8F97E8FD22651F6FA19F366DC3DE046C

Query result

Key Value
FileName./usr/bin/weka
FileSize116
MD5A11E79F973A2E95C4AB64CEF16AAAB4A
SHA-11FA781AD8F97E8FD22651F6FA19F366DC3DE046C
SHA-256F76033A00AB62655FD5374BEFB75AC7094CDA2EDFB99D559366EDFA595B6824F
SSDEEP3:TKH/xLWGv8TGI4RdlH+vQjUBEzErFHzr7+PX4:WoaIcCvexzAt2I
TLSHT17DB092F5B1002525E92E4674BA8B28D43690A4F49B04E99774D011C92FA2B4500E6A12
hashlookup:parent-total2
hashlookup:trust60

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Parents (Total: 2)

The searched file hash is included in 2 parent files which include package known and seen by metalookup. A sample is included below:

Key Value
MD5AC061703A460E873D11A166676578EA0
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
PackageRelease3.fc11
PackageVersion3.6.0
SHA-14C53147CAF0564A176B1EA678D6555E8FB02BEE4
SHA-2566B0197661494866799DA8F0516EBC13207C9B9549C0FECDF3BEA882963B174EA
Key Value
MD5A1904AF3DDF485ACCA318BAB2FEB70DB
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
PackageRelease4.fc12
PackageVersion3.6.0
SHA-19E36553C85D899DB44931A39F61F817BAD9F44D5
SHA-256C6806DD8B7140A3E6A8E0DA308178B1BD14B570F09305B8CDA27670430CC30AB