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NEW!   Debellor is being replaced now by Data Pipes, a Python framework for scalable processing of Big Data and Data Streams, more mature and functional than Debellor.


Debellor is an open source framework for scalable data mining and machine learning. You can implement your own algorithms in Debellor's architecture and combine them with pre-existing ones to create complex data processing networks and experimental setups. The unique feature of Debellor is data streaming, which enables efficient processing of massive data and is essential for scalability of algorithms. Debellor is used in TunedIT system for automated evaluation, benchmarking and comparison of learning algorithms.

Latest release can be downloaded here.


Debellor simplifies implementation of complex yet efficient algorithms.

Debellor is written in Java and distributed under GNU General Public Licence. Hosted by

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Debellor 1.0 can be downloaded here. The file contains Rseslib and Weka libraries, as well as example code (from org.debellor.example.Main in debellor.jar). Requires Java Runtime Environment (JRE) 1.6 or later.

To run the example, unzip the downloaded file and execute example.bat (on Windows) or (Linux). Note that on Linux you first have to set execution flag of the script, for example:

     chmod +x

Currently Debellor has no GUI, so you can use it only as a library of algorithms and a framework which defines base classes for your own algorithms (Cell) and data types (DataObject, DataType). Remember to put debellor.jar, plus optionally weka.jar and rseslib.jar (bundled in Debellor distribution) on CLASSPATH when compiling and executing your code. If you use IDE, for example Eclipse, you must include these JARs in dependencies for your project (in Eclipse, click Project -> Properties -> Java Build Path -> Libraries).

History of releases

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Debellor is developed by Marcin Wojnarski from Warsaw University, Faculty of Mathematics, Informatics and Mechanics, in cooperation with the research group led by Prof. Andrzej Skowron.


Please send all comments, questions, bugs... to: mwojnars (at)
Your feedback is very helpful in further development of Debellor.