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| FileName | ./usr/share/doc/weka-doc/doc/weka/core/NoSupportForMissingValuesException.html |
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| SHA-256 | 36C94C8196793F83BC16A2B07815EDAF373F6DBEBBAB5FC5495C7650D216734B |
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| 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 |
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