weka 3.6.14-4 source package in Ubuntu
Changelog
weka (3.6.14-4) unstable; urgency=medium * Team upload. [ Vladimir Petko ] * d/p/set_compiler_release.patch, d/rules: use java_compat_level variable provided by java-common to adjust -release level (Closes: #1053086) [ tony mancill ] * Update Homepage URL * Fix FTBFS twice in a row (Closes: #1046193) * Set Rules-Requires-Root: no in debian/control -- tony mancill <email address hidden> Sun, 03 Dec 2023 23:16:40 -0800
Upload details
- Uploaded by:
- Debian Java Maintainers
- Uploaded to:
- Sid
- Original maintainer:
- Debian Java Maintainers
- Architectures:
- all
- Section:
- science
- Urgency:
- Medium Urgency
See full publishing history Publishing
Series | Published | Component | Section | |
---|---|---|---|---|
Oracular | release | universe | science | |
Noble | release | universe | science |
Downloads
File | Size | SHA-256 Checksum |
---|---|---|
weka_3.6.14-4.dsc | 2.1 KiB | a39c7d2d2d0654a32a350221fee989d0a55ca5855efd241c5147a348ccc28a67 |
weka_3.6.14.orig.tar.gz | 13.9 MiB | bef592188ef4da3488c6043e782c6c8cea42877364d8a2be68d4d61b9a602368 |
weka_3.6.14-4.debian.tar.xz | 11.1 KiB | ac89291457bd4db93d78b83b81133f616574e01936755e4922f00be1d6a0ad36 |
Available diffs
- diff from 3.6.14-3 to 3.6.14-4 (1.5 KiB)
No changes file available.
Binary packages built by this source
- weka: 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.
- weka-doc: 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.