Augmented Visualization of Association Rules for Data Mining

نویسندگان

  • Wilson Andres Castillo Rojas
  • Claudio Meneses Villegas
  • Alexis Peralta
چکیده

This paper describes a proposal for enhanced visualization of a data-­‐mining model generated with Association Rule (AR) techniques by applying Self-­‐Organizing Maps (SOM). A representation of visual percep-­‐ tion model of AR based on a method called AVM-­‐DM (Augmented Visualiza-­‐ tion Models for Data Mining) is established, together with data and pat-­‐ terns, which support the visual exploration stage, thus fitting in the context of the KDD (Knowledge Discovery in Databases) process. This methodology seeks to answer generic user questions regarding the inner workings of the model, BLOCKIN BLOCKIN and BLOCKIN

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تاریخ انتشار 2014