WekaG is an extension of the Weka toolkit to a grid environment. Weka is a collection of machine learning algorithms for data mining tasks. It contains tools for all the data mining phases: data pre-processing, data mining tasks (e.g. classification, regression, clustering, association rules), and data post-processing. One important feature of this toolkit is the flexibility ofthis tool for developing new machine learning schemes. WekaG uses Globus as grid middleware.

WekaG offers two separate modules: (i) A server module, which is in charge of the creation of instances of data mining grid services by using a factory pattern. These grid services implement the functionality of every algorithm and stage of the data mining process; and (ii) A client module (API), which is responsible for contacting to a grid service.


Want to learn more about WekaG?

If you are interested in more details about the WekaG tool you can contact María S. Pérez.

public/wekag.txt · Last modified: 2010/11/18 13:30 by mperez
Trace: wekag

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