RM-Tool: A framework for discovering and evaluating association rules

نویسندگان

  • Cristóbal Romero
  • José María Luna
  • José Raúl Romero
  • Sebastián Ventura
چکیده

Nowadays, there are a great number of both specific and general data mining tools available to carry out association rule mining. However, it is necessary to use several of these tools in order to obtain only the most interesting and useful rules for a given problem and dataset. To resolve this drawback, this paper describes a fully integrated framework to help in the discovery and evaluation of association rules. Using this tool, any data mining user can easily discover, filter, visualize, evaluate and compare rules by following a helpful and practical guided process described in this paper. The paper also explains the results obtained using a sample public dataset. 2011 Elsevier Ltd. All rights reserved.

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عنوان ژورنال:
  • Advances in Engineering Software

دوره 42  شماره 

صفحات  -

تاریخ انتشار 2011