Divvy: fast and intuitive exploratory data analysis

  • Authors:

  • Joshua M. Lewis;Virginia R. De Sa;Laurens Van Der Maaten

  • Affiliations:

  • Department of Cognitive Science, University of California, San Diego, La Jolla, CA;Department of Cognitive Science, University of California, San Diego, La Jolla, CA;Faculty of Elect. Eng., Math., and Comp. Science, Delft University of Technology, Delft, The Netherlands

  • Venue:
  • The Journal of Machine Learning Research
  • Year:
  • 2013

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Abstract

Divvy is an application for applying unsupervised machine learning techniques (clustering and dimensionality reduction) to the data analysis process. Divvy provides a novel UI that allows researchers to tighten the action-perception loop of changing algorithm parameters and seeing a visualization of the result. Machine learning researchers can use Divvy to publish easy to use reference implementations of their algorithms, which helps themachine learning field have a greater impact on research practices elsewhere.