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

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

doi:10.1080/03081079.2013.798902

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 journal › Article › peer-review

20 Scopus citations

Abstract

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 language	English (US)
Pages (from-to)	614-634
Number of pages	21
Journal	International Journal of General Systems
Volume	42
Issue number	6
DOIs	https://doi.org/10.1080/03081079.2013.798902
State	Published - 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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10.1080/03081079.2013.798902

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AU - Hussain, Shahid

AU - Moshkov, Mikhail

AU - Zielosko, Beata

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

Abstract

Bibliographical note

ASJC Scopus subject areas

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