Optimization and analysis of decision trees and rules: Dynamic programming approach

Abdulaziz Alkhalid, Talha M. Amin, Igor Chikalov, Shahid Hussain, Mikhail Moshkov, Beata Zielosko

Research output: Contribution to journalArticlepeer-review

20 Scopus citations


This paper is devoted to the consideration of software system Dagger created in KAUST. This system is based on extensions of dynamic programming. It allows sequential optimization of decision trees and rules relative to different cost functions, derivation of relationships between two cost functions (in particular, between number of misclassifications and depth of decision trees), and between cost and uncertainty of decision trees. We describe features of Dagger and consider examples of this systems work on decision tables from UCI Machine Learning Repository. We also use Dagger to compare 16 different greedy algorithms for decision tree construction. © 2013 Taylor and Francis Group, LLC.
Original languageEnglish (US)
Pages (from-to)614-634
Number of pages21
JournalInternational Journal of General Systems
Issue number6
StatePublished - Aug 2013

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01

ASJC Scopus subject areas

  • Information Systems
  • Control and Systems Engineering
  • Modeling and Simulation
  • Computer Science Applications
  • Theoretical Computer Science


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