Result for 2D7B3729F0231C0B9DA757D9B41848B6E1CC9366

Query result

Key Value
FileName./usr/share/doc/weka/changelog.Debian.gz
FileSize918
MD5ABC7A446DE28C3258F3F3E608ED2D54C
SHA-12D7B3729F0231C0B9DA757D9B41848B6E1CC9366
SHA-2560B231A8623985580192698A04DE32947B91420C775D34414EB395E8C35198C90
SSDEEP24:XvjiWmkrjNMQXum9SKNpaiUa6bbQXzC0H6MKQQVZXzrRe:XvfHrZNXpNpaLj+z96LFVZXzrRe
TLSHT19A11883A76BDA471790051DDE56C4EC109878644E9C27DCC6F5D7505742F40C2248F3D
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
FileSize7218182
MD506D48686F139062C279D8E87C6648FEE
PackageDescriptionMachine learning algorithms for data mining tasks Weka is a collection of machine learning algorithms in Java that can either be used from the command-line, or called from your own Java code. Weka is also ideally suited for developing new machine learning schemes. . Implemented schemes cover decision tree inducers, rule learners, model tree generators, support vector machines, locally weighted regression, instance-based learning, bagging, boosting, and stacking. Also included are clustering methods, and an association rule learner. Apart from actual learning schemes, Weka also contains a large variety of tools that can be used for pre-processing datasets. . This package contains the binaries and examples.
PackageMaintainerUbuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com>
PackageNameweka
PackageSectionscience
PackageVersion3.6.13-1
SHA-19ED5CEF0A52B33F3F967E5D418C219C5759319F6
SHA-256AC823BD17B2D411B4A251CFFBAAB8EB483D006833C2729BEB5190B9697CD3446