A Comparative Analysis of different classes-interpretation support techniques

  • Authors:
  • Karina Gibert;Alejandra Perez-Bonilla;Gustavo Rodriguez-Silva

  • Affiliations:
  • Department of Statistics and Operations Research. Universitat Politènica de Catalunya. Campus Nord, Edif. C5, C. Jordi Girona 1-3, 08034 --Barcelona. e-mail: karina.gibert@upc.edu;Department of Statistics and Operations Research. Universitat Politènica de Catalunya. Campus Nord, Edif. C5, C. Jordi Girona 1-3, 08034 --Barcelona. e-mail: karina.gibert@upc.edu;Department of Statistics and Operations Research. Universitat Politènica de Catalunya. Campus Nord, Edif. C5, C. Jordi Girona 1-3, 08034 --Barcelona. e-mail: karina.gibert@upc.edu

  • Venue:
  • Proceedings of the 2006 conference on Artificial Intelligence Research and Development
  • Year:
  • 2006

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Abstract

In this work, the application of some traditional statistical or AI techniques (Logistic Regression, Decision Trees and Discriminant Analysis) used to assist interpretation of a set of classes is presented together with a new methodology Conceptual characterization by embedded conditioning (CCEC)[7] based on combination of statistics and some knowledge induction. All of them are applied to a set of real data coming from a WasteWater Treatment Plant (WWTP) previously classified [8] to identify the characteristic situations that can be found in.