Binary package “weka-doc” in ubuntu xenial
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.
Source package
Published versions
- weka-doc 3.6.13-1 in amd64 (Proposed)
- weka-doc 3.6.13-1 in amd64 (Release)
- weka-doc 3.6.13-1 in arm64 (Proposed)
- weka-doc 3.6.13-1 in arm64 (Release)
- weka-doc 3.6.13-1 in armhf (Proposed)
- weka-doc 3.6.13-1 in armhf (Release)
- weka-doc 3.6.13-1 in i386 (Proposed)
- weka-doc 3.6.13-1 in i386 (Release)
- weka-doc 3.6.13-1 in powerpc (Proposed)
- weka-doc 3.6.13-1 in powerpc (Release)
- weka-doc 3.6.13-1 in ppc64el (Proposed)
- weka-doc 3.6.13-1 in ppc64el (Release)
- weka-doc 3.6.13-1 in s390x (Release)