Abstract
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.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Delimata, P., Moshkov, M.J., Skowron, A., Suraj, Z. (2009). Classifiers Based on Deterministic and Inhibitory Decision Rules. In: Inhibitory Rules in Data Analysis. Studies in Computational Intelligence, vol 163. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85638-2_6
Download citation
DOI: https://doi.org/10.1007/978-3-540-85638-2_6
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-85637-5
Online ISBN: 978-3-540-85638-2
eBook Packages: EngineeringEngineering (R0)