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View Full Version : New Weka 3.4.13 and 3.5.8 releases



Mark
07-16-2008, 12:08 AM
Hi everybody!

New versions of Weka are available for download from the Weka homepage or directly from SourceForge :

* Weka 3.4.13 - the book version available as ZIP, Win32 installer, Win32 installer incl. JRE 1.4.2_13 and Mac OS X application.

* Weka 3.5.8 - the developer version available as ZIP, with Win32 installer, Win32 installer incl. JRE 1.5.0_16 and Mac OS X application.

Both versions contain a significant number of bugfixes, it is recommended to upgrade to the new versions. The documentation on the WekaDoc Wiki on Sourceforge.net and the Pentaho micro site (weka.pentaho.org) will be updated soon.

Weka homepage:
http://www.cs.waikato.ac.nz/~ml/weka/

SourceForge site:
http://sourceforge.net/projects/weka/

Note:
It might take a while before Sourceforge.net has propagated all the files to its mirrors.


What's new in the developer version?

Some highlights
---------------
* New classifiers: Bayesian logistic regression, discriminitive multinomial naive Bayes for text classification, functional trees and decision table-naive Bayes hybrid.
* SubsetByExpression filter.
* Latent semantic analysis.
* Improved output in Logistic, NaiveBayes, EM and SimpleKMeans.
* Plugin support for the KnowledgeFlow.
* Ability to execute knowledge flows outside of the GUI.
* Output predictions for a run of cross-validation and percentage split on the command line.
* Instance weights can now be specified in a standard ARFF file.
* Cost sensitive attribute selection.

New classes:
weka.attributeSelection.ASEvaluation:
weka.attributeSelection.CostSensitiveAttributeEval
weka.attributeSelection.CostSensitiveSubsetEval
weka.attributeSelection.FilteredAttributeEval
weka.attributeSelection.FilteredSubsetEval
weka.attributeSelection.LatentSemanticAnalysis

weka.classifiers.Classifier:
weka.classifiers.bayes.BayesianLogisticRegression
weka.classifiers.bayes.DMNBtext
weka.classifiers.rules.DTNB
weka.classifiers.trees.FT

weka.core.DistanceFunction:
weka.core.EditDistance

weka.clusterers.Clusterer:
weka.clusterers.CLOPE
weka.clusterers.sIB

weka.classifiers.functions.supportVector.Kernel:
weka.classifiers.functions.supportVector.PrecomputedKernelMatrixKernel

weka.experiment.SplitEvaluator:
weka.experiment.DensityBasedClustererSplitEvaluator

weka.associations.Associator:
weka.associations.HotSpot

weka.filters.Filter:
weka.filters.unsupervised.instance.SubsetByExpression


As usual, for a complete list of changes refer to
the changelogs.

Cheers,
The Weka Team