Classifiers Based on Deterministic and Inhibitory Decision Rules

Part of the Studies in Computational Intelligence book series (SCI, volume 163)


In this chapter, we consider the following problem of classification (prediction): for a decision table T and a new object v, given by values of conditional attributes from T, it is required to generate a decision corresponding to v.

We compare qualities of classifiers based on exact deterministic and inhibitory decision rules.

The first type of classifiers is the following: for a given decision table we construct for each row an exact deterministic decision rule using the greedy algorithm. The obtained system of rules jointly with simple procedure of voting can be considered as a classifier. A deterministic rule, which is realizable for given object, is a vote “pro” the decision from the right-hand side of the rule.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  1. 1.University of RzeszowPoland
  2. 2.University of Silesia, SosnowiecPoland
  3. 3.Warsaw University, WarsawPoland

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