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FlexDM: Simple, parallel and fault-tolerant data mining using WEKA.

Madison Flannery1, David M Budden1, Alexandre Mendes2

  • 1Systems Biology Laboratory, University of Melbourne, Parkville, 3010 VIC Australia.

Source Code for Biology and Medicine
|November 19, 2015
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Summary
This summary is machine-generated.

FlexDM enhances the WEKA framework to simplify large-scale data mining and machine learning experiments. This new software addresses WEKA

Keywords:
Data miningJavaMachine learningWEKAXML

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Area of Science:

  • Data Science
  • Machine Learning
  • Bioinformatics

Background:

  • Exponential data growth necessitates efficient large-scale data mining and machine learning for researchers lacking programming expertise.
  • The Waikato Environment for Knowledge Analysis (WEKA) is a widely used framework simplifying these tasks via its Experimenter GUI.
  • However, WEKA's Experimenter has limitations in schema verbosity, hyper-parameter optimization, experiment recovery, and multicore utilization.

Purpose of the Study:

  • To introduce FlexDM, a novel software extension designed to overcome the limitations of the WEKA Experimenter.
  • To provide a more efficient, robust, and scalable solution for complex data mining and machine learning experiments.

Main Methods:

  • FlexDM replaces WEKA's verbose XML schema with a more concise and manageable format.
  • It enables meta-optimization of experiments across numerous algorithm hyper-parameters.
  • The software incorporates fault tolerance for uninterrupted execution during large-scale experiments and leverages multicore processors for parallel task execution.

Main Results:

  • FlexDM's schema is 10 times shorter than WEKA's default, offering finer control over experimental procedures.
  • Tested on a large biological dataset, FlexDM demonstrated stability and automatic parallelization, achieving quasi-linear speedup on multicore architectures.
  • Execution time reduction was significant when tasks were distributed across multiple processor cores.

Conclusions:

  • FlexDM is a powerful, user-friendly extension that significantly improves upon the WEKA package for handling modern data volumes and complexity.
  • It enhances productivity for research groups performing large-scale data mining and machine learning, offering non-programmers greater control via a simplified schema.
  • FlexDM is cross-platform (Windows, OSX, Linux) and available as a pre-configured virtual environment for easy deployment and extensibility.