Extensions of dynamic programming as a new tool for decision tree optimization

Abdulaziz Alkhalid, Igor Chikalov, Shahid Hussain, Mikhail Moshkov

Research output: Contribution to journalArticlepeer-review

15 Scopus citations


The chapter is devoted to the consideration of two types of decision trees for a given decision table: α-decision trees (the parameter α controls the accuracy of tree) and decision trees (which allow arbitrary level of accuracy). We study possibilities of sequential optimization of α-decision trees relative to different cost functions such as depth, average depth, and number of nodes. For decision trees, we analyze relationships between depth and number of misclassifications. We also discuss results of computer experiments with some datasets from UCI ML Repository. ©Springer-Verlag Berlin Heidelberg 2013.
Original languageEnglish (US)
Pages (from-to)11-29
Number of pages19
JournalSmart Innovation, Systems and Technologies
StatePublished - 2013

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01

ASJC Scopus subject areas

  • General Computer Science
  • General Decision Sciences


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