诱导倾斜决策树

R. Struharik, Vuk Vranjkovic, S. Dautovic, L. Novak
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引用次数: 10

摘要

本文介绍了进化算法在斜决策树推理中的应用。新决策树诱导算法的核心是称为HereBoy的特定进化算法。利用UCI Machine Learning Repository数据库中获得的标准基准数据集,研究了所提出的HBDT算法的性能,并与现有的八种决策树构建算法进行了比较。实验研究结果表明,所提出的HBDT算法与先前提出的一些决策树构建算法相比具有较好的优势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Inducing oblique decision trees
In this paper an application of evolutionary algorithm to oblique decision tree inference is presented. In the core of new decision tree inducing algorithm is the specific evolutionary algorithm called HereBoy. Performance of proposed HBDT algorithm is studied and compared with eight existing decision tree building algorithms using standard benchmark datasets obtained from the UCI Machine Learning Repository database. The results of experimental study indicate that the proposed HBDT algorithm compares very favorably with some of the previously proposed decision tree building algorithms.
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