In this chapter, we consider algorithms which construct the sets of Pareto optimal points for bi-criteria optimization problems for decision (inhibitory) rules and rule systems relative to a cost function and an uncertainty (completeness) measure. We show how the constructed set of Pareto optimal points can be transformed into the graphs of functions which describe the relationships between the considered cost function and uncertainty (completeness) measure. Computer experiments provide us with examples of trade-off between complexity and accuracy for decision and inhibitory rule systems.
|Original language||English (US)|
|Title of host publication||Intelligent Systems Reference Library|
|Publisher||Springer Science and Business Media Deutschland GmbH|
|Number of pages||17|
|State||Published - 2020|
|Name||Intelligent Systems Reference Library|
Bibliographical notePublisher Copyright:
© 2020, Springer Nature Switzerland AG.
ASJC Scopus subject areas
- Computer Science(all)
- Information Systems and Management
- Library and Information Sciences