Evolutionary approach for automated component-based decision tree algorithm design

作     者：Jovanovic, Milos Delibasic, Boris Vukicevic, Milija Suknovic, Milija Martic, Milan 

作者机构：Univ Belgrade Fac Org Sci Belgrade Serbia 

出 版 物：《INTELLIGENT DATA ANALYSIS》 (智能数据分析)

年 卷 期：2014年第18卷第1期

页      面：63-77页

核心收录：

学科分类：08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：Serbian Ministry of Science and Technological Development [III 47003] 

主　　题：Decision tree classification evolutionary algorithm automated algorithm design reusable components component-based algorithms 

摘      要：This paper proposes a framework for automated design of component-based decision tree algorithms. These algorithms are being constructed by interchanging components extracted from decision tree algorithms and their partial improvements. Manual selection of the best-suited algorithm for a specific problem is a complex task because of the huge algorithmic space derived from component-based design. The proposed framework searches through the algorithmic space with an evolutionary algorithm by interchanging components and tuning parameters, and finds a near optimal algorithm for a specific problem. Through experiments we show that using this meta-heuristic is justified in automated component-based algorithm design. This approach is useful not only as an algorithm design help, but also as a technology enhanced learning tool, which aids the understanding of the algorithms.