Machine learning algorithms for data mining tasks
DescriptionWeka 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.
7336 other people were interested in this package here. The newest known version of this software is 3.6.14-1 (Information last updated about 20 hours ago.)
Upload new screenshots
Thanks for uploading more screenshots. Please note:
- Your screenshot should contain a typical scene when working with it.
- Take only a screenshot of the respective application and not of your whole desktop (unless the screenshot is meant for a window manager).
- Your screenshots must be in PNG format.
- You can upload multiple images at once.
- Your screenshot need to be approved by the moderators first. You will already see your screenshot but it will not be visible to others instantly. If moderators reject your upload you will get notified next time you visit this site (requires cookies).
- Images larger than 800x600 pixels will automatically be reduced. So don't try to capture too much detail in a screenshot. It may become unreadable. Shrink the applications window if possible.
- Screenshots are made public and can freely be used by anyone.
- Useful programs for making screenshots are shutter, ksnapshot (KDE), gimp, xwd or scrot. See the Debian wiki for more information on how to make screenshots under Debian.
- Please set your language to english so that everybody understands it. If you don't use english by default please start your application from a shell using after setting "export LANG=C".