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

被引：12

作者：

Alkhalid, Abdulaziz ^{[1
]}

Amin, Talha ^{[2
]}

Chikalov, Igor ^{[2
]}

Hussain, Shahid ^{[2
]}

Moshkov, Mikhail ^{[2
]}

Zielosko, Beata ^{[2
,3
]}

机构：

[1] Carleton Univ, Dept Syst & Comp Engn, Ottawa, ON K1S 5B6, Canada

[2] King Abdullah Univ Sci & Technol, Comp Elect & Math Sci & Engn Div, Thuwal, Saudi Arabia

[3] Univ Silesia, Inst Comp Sci, Sosnowiec, Poland

来源：

INTERNATIONAL JOURNAL OF GENERAL SYSTEMS | 2013年 / 42卷 / 06期

关键词：

dynamic programming; decision trees; decision rules; optimization; ALGORITHMS; INDUCTION;

D O I：

10.1080/03081079.2013.798902

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

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 system's work on decision tables from UCI Machine Learning Repository. We also use Dagger to compare 16 different greedy algorithms for decision tree construction.

引用

页码：614 / 634

页数：21

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