Welcome to my BenchMarking Via Weka project page.

On this web page you will find software to download and documentation about this new programming-language agnostic experimental framework.
Though this framework uses Weka as a backend on the server-side, the clients are completely independent of the Weka framework. This makes it easy to develop clients for any programming language, one only needs to implement the client-server communication protocol.
So far, a Java and Python client have been implemented. And yes, there's also a plugin available that makes all the Weka classifiers available on the client side.

Latest News

NIPS 2008: MLOSS workshop - 2008-12-12 17:55 PST - FracPete
I presented BMVW at the NIPS 2008 workshop on Machine Learning Open Source Software. At one point, the presentation will be available on videolectures.net.

Version 0.0.4 released - 2008-12-04 11:24 NZ - FracPete
The releases come in quick succession now... Just released version 0.0.4. It contains a few bugfixes along some new functionality, e.g., re-running the last experiment setup that was used (handy, if one forgot to check "Submit"), selecting multiple datasets for displaying comments, data, etc.
Admins can now also delete datasets from the database (either from the command-line with the deleteDataset command or via the GUI in the datasets overview).
You can grab it from the downloads section as usual.

Version 0.0.3 released - 2008-12-02 16:10 NZ - FracPete
Version 0.0.3 is now officially released. It is mainly a bugfix release, with the most import fix: experiments are not longer submitted incorrectly on multi-core machines.
In addition to that, admins can now also delete experiments from the database (either from the command-line with the deleteExperiment command or via the GUI in the experiments overview).
You can grab it from the downloads section as usual.

Release 0.0.2 is out of the door! - 2008-10-01 11:22 NZ - FracPete
Just released version 0.0.2 of the framework!! You can grab it from the downloads section as usual. This release contains decent documentation for the user and the developer (how to implement new schemes/filter or clients in other languages).

I've also created an entry on mloss.org. Check it out! :-)


All news...