Result for 04F423D7434A3DE8C930D5444368287AC9797842

Query result

Key Value
FileName./usr/share/icons/hicolor/32x32/apps/weka.png
FileSize2179
MD579BAE888950DD5C6CBFC82AF349A36CE
SHA-104F423D7434A3DE8C930D5444368287AC9797842
SHA-256816CBAB0E17C838F7CFC8BA050DFE25A76D67D8904E71501C0DA4BE8A0FA1B36
SSDEEP48:vm6IP1vKPReGabSfEVdeCze9PcpYK/x2MiXB5UN9/QZMU77NErMEG:vR+1buEOiiPGIvB5o/YMU77Nl
TLSHT1F1412BF32198F254E50A837D61373BB5FDE1E5BB156903E0A79491301A443D419CDF40
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
MD5EA74E950EC5AA4A7ED2034FDA6C84F78
PackageArchnoarch
PackageDescriptionWeka is a collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a data-set 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
PackageRelease2.fc24
PackageVersion3.6.13
SHA-159DABF4634BC1455F0829472D885642D723CB691
SHA-25643E9B28D52B8E0FDA22EB4285AAD30FB1B571878FF6E71B0661FD2559796AE3A
Key Value
MD58D60C7723EDE350E152877581A1947F0
PackageArchnoarch
PackageDescriptionWeka is a collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a data-set 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
PackageRelease2.fc24
PackageVersion3.6.13
SHA-1DAA2D46E065CE230E1C485F9784F098F3569C010
SHA-256901DA0DF8A4EDAD93E9C0E8A28C9A13591679F6340FF8CF2AFC7385C5203B86D