On Algorithm for Building of Optimal α-Decision Trees

被引：0
|
作者：
Alkhalid, Abdulaziz [1 ]
Chikalov, Igor [1 ]
Moshkov, Mikhail [1 ]
机构：
[1] King Abdullah Univ Sci & Technol, Math & Comp Sci & Engn Div, Thuwal 239556900, Saudi Arabia
来源：
ROUGH SETS AND CURRENT TRENDS IN COMPUTING, PROCEEDINGS | 2010年 / 6086卷
关键词：
Decision tree; dynamic programming; algorithm complexity;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The paper describes an algorithm that constructs approximate decision trees (alpha-decision trees), which are optimal relatively to one of the following complexity measures: depth, total path length or number of nodes. The algorithm uses dynamic programming and extends methods described in [4] to constructing approximate decision trees. Adjustable approximation rate allows controlling algorithm complexity. The algorithm is applied to build optimal alpha-decision trees for two data sets from UCI Machine Learning Repository [1].
引用
收藏
页码：438 / 445
页数：8
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