| Key | Value |
|---|---|
| FileName | ./usr/share/icons/hicolor/32x32/apps/weka.png |
| FileSize | 2179 |
| MD5 | 79BAE888950DD5C6CBFC82AF349A36CE |
| SHA-1 | 04F423D7434A3DE8C930D5444368287AC9797842 |
| SHA-256 | 816CBAB0E17C838F7CFC8BA050DFE25A76D67D8904E71501C0DA4BE8A0FA1B36 |
| SSDEEP | 48:vm6IP1vKPReGabSfEVdeCze9PcpYK/x2MiXB5UN9/QZMU77NErMEG:vR+1buEOiiPGIvB5o/YMU77Nl |
| TLSH | T1F1412BF32198F254E50A837D61373BB5FDE1E5BB156903E0A79491301A443D419CDF40 |
| hashlookup:parent-total | 2 |
| hashlookup:trust | 60 |
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 |
|---|---|
| MD5 | EA74E950EC5AA4A7ED2034FDA6C84F78 |
| PackageArch | noarch |
| PackageDescription | Weka 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. |
| PackageMaintainer | Fedora Project |
| PackageName | weka |
| PackageRelease | 2.fc24 |
| PackageVersion | 3.6.13 |
| SHA-1 | 59DABF4634BC1455F0829472D885642D723CB691 |
| SHA-256 | 43E9B28D52B8E0FDA22EB4285AAD30FB1B571878FF6E71B0661FD2559796AE3A |
| Key | Value |
|---|---|
| MD5 | 8D60C7723EDE350E152877581A1947F0 |
| PackageArch | noarch |
| PackageDescription | Weka 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. |
| PackageMaintainer | Fedora Project |
| PackageName | weka |
| PackageRelease | 2.fc24 |
| PackageVersion | 3.6.13 |
| SHA-1 | DAA2D46E065CE230E1C485F9784F098F3569C010 |
| SHA-256 | 901DA0DF8A4EDAD93E9C0E8A28C9A13591679F6340FF8CF2AFC7385C5203B86D |