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A Sensitivity Analysis for Quality Measures of Quantitative Association Rules

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8073)

Abstract

There exist several fitness function proposals based on a combination of weighted objectives to optimize the discovery of association rules. Nevertheless, some differences in the measures used to assess the quality of association rules could be obtained according to the values of such weights. Therefore, in such proposals it is very important the user’s decision in order to specify the weights or coefficients of the optimized objectives. Thus, this work presents an analysis on the sensitivity of several quality measures when the weights included in the fitness function of the existing QARGA algorithm are modified. Finally, a comparative analysis of the results obtained according to the weights setup is provided.

Keywords

Data mining sensitivity analysis quantitative association rules quality measures 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Department of Computer ScienceUniversity of SevilleSpain
  2. 2.Department of Computer SciencePablo de Olavide University of SevilleSpain

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