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Instance Selection in Logical Rule Extraction for Regression Problems

  • Mirosław Kordos
  • Szymon Białka
  • Marcin Blachnik
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7895)

Abstract

The paper presents three algorithms of instance selection for regression problems, which extend the capabilities of the CNN, ENN and CA algorithms used for classification tasks. Various combinations of the algorithms are experimentally evaluated as data preprocessing for regression tree induction. The influence of the instance selection algorithms and their parameters on the accuracy and rules produced by regression trees is evaluated and compared to the results obtained with tree pruning.

Keywords

Regression Tree Regression Problem Logical Rule Instance Selection Tree Pruning 
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 2013

Authors and Affiliations

  • Mirosław Kordos
    • 1
  • Szymon Białka
    • 1
  • Marcin Blachnik
    • 2
  1. 1.Department of Mathematics and Computer ScienceUniversity of Bielsko-BialaBielsko-BiałaPoland
  2. 2.Department of Management and InformaticsSilesian University of TechnologyKatowicePoland

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