Subscribe to DSC Newsletter

Evaluation and comparison of open source software suites for data mining and knowledge discovery

An article by A.H.Abdulrahman, J. M. Luna, 2 M. A. Vallejo 3 and S. Ventura with the title "Evaluation and comparison of open source software suites for data mining and knowledge discovery" (published by Wiley "Data Mining and Knowledge Discovery, Vol 7 Issue 3 2017 see this link) provides the research community with an extensive study on different features included in any data mining tool. The final score for usability, as for 2017, looks as this:

The conclusion of this study is "RapidMiner, KNIME, and  WEKA appear as the most promising open source data mining tools on a basis of the two specific evaluation procedures"

A few comments for this analysis approach may follow: the above consideration did not include the R project, and it seems favors Java-based software. Also, there is no distinction between "application", "framework" or "environment". For example, DataMelt is an environment, rather than a self-contained application, and it also includes Weka as an additional external package used in the DataMelt scripting environment for data scientists.

Views: 597

Comments are closed for this blog post

Videos

  • Add Videos
  • View All

Follow Us

© 2018   Data Science Central ®   Powered by

Badges  |  Report an Issue  |  Privacy Policy  |  Terms of Service