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| PackageDescription | documentation for the Weka machine learning suite 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 | Debian Java Maintainers <pkg-java-maintainers@lists.alioth.debian.org> |
| PackageName | weka-doc |
| PackageSection | doc |
| PackageVersion | 3.6.14-2 |
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| 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 binaries and examples. |
| PackageMaintainer | Debian Java Maintainers <pkg-java-maintainers@lists.alioth.debian.org> |
| PackageName | weka |
| PackageSection | science |
| PackageVersion | 3.6.14-2 |
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