Assessing Classification Accuracy in the Revision Stage of a CBR Spam Filtering System

  • José Ramón Méndez
  • Carlos González
  • Daniel Glez-Peña
  • Florentino Fdez-Riverola
  • Fernando Díaz
  • Juan Manuel Corchado
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4626)


In this paper we introduce a quality metric for characterizing the solutions generated by a successful CBR spam filtering system called SpamHunting. The proposal is denoted as relevant information amount rate and it is based on combining estimations about relevance and amount of information recovered during the retrieve stage of a CBR system. The results obtained from experimentation show how this measure can successfully be used as a suitable complement for the classifications computed by our SpamHunting system. In order to evaluate the performance of the quality estimation index, we have designed a formal benchmark procedure that can be used to evaluate any accuracy metric. Finally, following the designed test procedure, we show the behaviour of the proposed measure using two well-known publicly available corpus.


Receiver Operating Characteristic Feature Selection Receiver Operating Characteristic Curve Receiver Operating Characteristic Analysis Negative Likelihood Ratio 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • José Ramón Méndez
    • 1
  • Carlos González
    • 2
  • Daniel Glez-Peña
    • 1
  • Florentino Fdez-Riverola
    • 1
  • Fernando Díaz
    • 3
  • Juan Manuel Corchado
    • 4
  1. 1.Dept. Informática, University of Vigo, Escuela Superior de Ingeniería Informática, Edificio Politécnico, Campus Universitario As Lagoas s/n, 32004, OurenseSpain
  2. 2.GFI Informatique, C/ Salvatierra 5, 28034, MadridSpain
  3. 3.Dept. Informática, University of Valladolid, Escuela Universitaria de Informática, Plaza Santa Eulalia, 9-11, 40005, SegoviaSpain
  4. 4.Dept. Informática y Automática, University of Salamanca, Plaza de la Merced s/n, 37008, SalamancaSpain

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