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|---|---|
| FileName | ./usr/share/doc/weka-doc/doc/weka/gui/graphvisualizer/package-tree.html |
| FileSize | 8360 |
| MD5 | 16D3805EFD47D888C60E7321EDF1715A |
| SHA-1 | 00CC39937E80205E89657197A367B5AD1C8C1A74 |
| SHA-256 | 347FD1EADBF01547064B0FDC98ACE5CA91F37580F740885E923E5A847BB77621 |
| SSDEEP | 192:fSX+0Fici6HbJ1+RshxUGMpjnQsvZici7:A1Fici67J1+RaxUGMpztvZici7 |
| TLSH | T1A502DE16D958BC12034A468489B90EB277C3C722FE7AADC9F2BDE125EC11FD15C18D9B |
| hashlookup:parent-total | 1 |
| hashlookup:trust | 55 |
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 |
|---|---|
| FileSize | 4741684 |
| MD5 | D03BBD5911AA088145547AE1D9410E90 |
| PackageDescription | Machine 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 documentation. |
| PackageMaintainer | Ubuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com> |
| PackageName | weka-doc |
| PackageSection | doc |
| PackageVersion | 3.6.10-2 |
| SHA-1 | 0DCB2C9F7011EBB669E1187794E206613866FBBF |
| SHA-256 | 24B836F62CCB7CFCDF8BAE300165E1DD6FD9D89FBD18DFA248BE22876C9A2A17 |