Hi everyone!

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

* Weka 3.6.6 - stable book 3rd edition version. It is available as ZIP, with Win32 installer, Win32 installer incl. JRE 1.6.0_21, Win64 installer, Win64 installer incl. 64 bit JRE 1.6.0_21 and Mac OS X application.

* Weka 3.7.5 - development version. It is available as ZIP, with Win32 installer, Win32 installer incl. JRE 1.6.0_21, Win64 installer, Win64 installer incl. 64 bit JRE 1.6.0_21 and Mac OS X application.

Both versions contain a significant number of bugfixes, it is recommended to upgrade to the new versions. Stable Weka 3.6 receives bug fixes only. The development version receives bug fixes and new features.

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

Pentaho data mining community documentation:
http://wiki.pentaho.com/display/DATA...+Documentation

Packages for Weka>=3.7.2 can be browsed online at:
http://weka.sourceforge.net/packageMetaData/

The Pentaho Weka micro site at http://weka.pentaho.com/ will be updated to reflect the new releases soon.

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

What's new in 3.7.5?

Some highlights
---------------

In core weka:

* weka.classifiers.functions.SGDText - stochastic gradient descent for learning linear SVMs and logistic regression for text problems. Operates incrementally and directly on string attributes.
* New incremental version of the multi-class meta classifier (weka.classifiers.meta.MultiClassClassifierUpdateable).
* RandomForest now supports building trees in parallel.
* DatabaseLoader is now much faster when loading data sets with many nominal attributes.
* Database access now allows custom property files to be set at runtime, allowing access to databases different from the default one without having to restart Weka.
* TextDirectoryLoader can now operate incrementally.
* CSVLoader now supports files without a header row.
* Charts can now be exported to files from running Knowledge Flow processes via an offscreen rendering process.
* RemoveUseless filter now removes attributes with all missing values.
* Histogram visualization in the Explorer and Knowledge Flow is now faster.
* ClassifierPerformanceEvaluator in the Knowledge Flow is now multi-threaded to allow folds to be evaluated in parallel.
* File-based savers now support gzip compression.
* File-based loaders now support loading files as a resource from the classpath (including jars).


In packages:
* multiInstanceLearning - added MITI multi-instance tree learner and MIRI rule learner variant.
* RerankingSearch - a feature selection meta-search algorithm that speeds up the base search algorithm, contributed by Pablo Bermejo.
* timeseriesForecasting package now includes support for handling timestamp-based data which contains gaps in the regular time period.
* sasLoader - SAS sas7bdat file reader.
* CHIRP - A new classifier based on Composite Hypercubes on Iterated Random Projections, contributed by Leland Wilkinson.
* PSOSearch - An implementation of the Particle Swarm Optimization (PSO) algorithm to explore the space of attributes, contributed by Sebastian Luna Valero.
* wekaServer - A simple servlet-based server for executing data mining tasks (Explorer and KnowledgeFlow so far). Docs at URL=http://wiki.pentaho.com/display/DATAMINING/Weka+Server
*jfreechartOffscreenRenderer - Offscreen (headless) chart rendering in Knowledge Flow processes using the JFreeChart library.


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

Cheers,
The Weka Team.