In this chapter, we study bi-criteria optimization problem cost versus cost for decision and inhibitory trees. We design an algorithm which constructs the set of Pareto optimal points for bi-criteria optimization problem for decision trees, and show how the constructed set can be transformed into the graphs of functions that describe the relationships between the studied cost functions. We extend the obtained results to the case of inhibitory trees. We consider two applications: study of 12 greedy heuristics as algorithms for single- and bi-criteria optimization of decision and inhibitory trees, and study of two relationships for decision trees related to knowledge representation—number of nodes versus depth and number of nodes versus average depth.
|Original language||English (US)|
|Title of host publication||Intelligent Systems Reference Library|
|Publisher||Springer Science and Business Media Deutschland GmbH|
|Number of pages||19|
|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