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Published August 3, 2015 | Version v1
Software Open

FlexDM Virtual Reference Environment

  • 1. Systems Biology Laboratory, University of Melbourne, Australia
  • 2. School of Electrical Engineering and Computer Science, The University of Newcastle, Australia

Description

With the continued exponential growth in data volume, large-scale data mining and machine learning experiments have become a necessity for many researchers without programming or statistics backgrounds. WEKA (Waikato Environment for Knowledge Analysis) is a gold standard framework that facilitates and simplifies this task. FlexDM addresses four fundamental limitations with the WEKA Experimenter: reliance on a verbose and difficult-to-modify XML schema; inability to meta-optimise experiments over a large number of algorithm hyper-parameters; inability to recover from software or hardware failure during a large experiment; and failing to leverage modern multicore processor architectures.

FlexDM is a powerful and easy-to-use extension to the WEKA package, which better handles the increased volume and complexity of data that has emerged during the 20 years since WEKA’s original development. FlexDM has been tested on Windows, OSX and Linux operating systems and is provided here as a pre-configured virtual reference environment for trivial usage and extensibility. 

Files

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Additional details

References

  • Flannery, M., Budden, D. M., & Mendes, A. (2014). FlexDM: Enabling robust and reliable parallel data mining using WEKA. arXiv preprint arXiv:1412.5720.