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An Integer Programming Approach to Inductive Learning Using Genetic and Greedy Algorithms

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New Learning Paradigms in Soft Computing

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 84))

Abstract

In this paper we propose an improved inductive learning method, IP2, to derive classification rules that correctly describe most of the examples belonging to a class and do not describe most of the examples not belonging to this class. A pre-analysis of data is included that assigns higher weights to those values of attributes which occur more often in the positive than in the negative examples. The inductive learning problem is represented as a modification of the set covering problem which are solved by an integer programming based algorithm using elements of a greedy algorithm or a genetic algorithm. The results are very encouraging and are illustrated on thyroid cancer and coronary heard disease problems.

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Author information

Authors and Affiliations

  1. Systems Research Institute, Polish Academy of Sciences, ul. Newelska 6, 01-447, Warsaw, Poland

    Janusz Kacprzyk & Grażyna Szkatuła

Authors
  1. Janusz Kacprzyk
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  2. Grażyna Szkatuła
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Editor information

Editors and Affiliations

  1. Knowledge-Based Intelligent Engineering Systems Centre, University of South Australia, 5095, Adelaide, Mawson Lakes, South Australia, Australia

    Lakhmi C. Jain

  2. Systems Research Institute, Polish Academy of Sciences, ul. Newelska 6, 01-447, Warsaw, Poland

    Janusz Kacprzyk

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© 2002 Springer-Verlag Berlin Heidelberg

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Kacprzyk, J., Szkatuła, G. (2002). An Integer Programming Approach to Inductive Learning Using Genetic and Greedy Algorithms. In: Jain, L.C., Kacprzyk, J. (eds) New Learning Paradigms in Soft Computing. Studies in Fuzziness and Soft Computing, vol 84. Physica, Heidelberg. https://doi.org/10.1007/978-3-7908-1803-1_11

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  • DOI: https://doi.org/10.1007/978-3-7908-1803-1_11

  • Publisher Name: Physica, Heidelberg

  • Print ISBN: 978-3-7908-2499-5

  • Online ISBN: 978-3-7908-1803-1

  • eBook Packages: Springer Book Archive

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