Podgorelec Vili, Kokol Peter, Stiglic Milojka Molan, Hericko Marjan, Rozman Ivan
University of Maribor - FERI, Smetanova 17, SI-2000 Maribor, Slovenia.
Comput Methods Programs Biomed. 2005 Dec;80 Suppl 1:S39-49. doi: 10.1016/s0169-2607(05)80005-7.
In this paper we study an evolutionary machine learning approach to data mining and knowledge discovery based on the induction of classification rules. A method for automatic rules induction called AREX using evolutionary induction of decision trees and automatic programming is introduced. The proposed algorithm is applied to a cardiovascular dataset consisting of different groups of attributes which should possibly reveal the presence of some specific cardiovascular problems in young patients. A case study is presented that shows the use of AREX for the classification of patients and for discovering possible new medical knowledge from the dataset. The defined knowledge discovery loop comprises a medical expert's assessment of induced rules to drive the evolution of rule sets towards more appropriate solutions. The final result is the discovery of a possible new medical knowledge in the field of pediatric cardiology.
在本文中，我们研究了一种基于分类规则归纳的数据挖掘和知识发现的进化机器学习方法。介绍了一种名为AREX的自动规则归纳方法，该方法使用决策树的进化归纳和自动编程。所提出的算法应用于一个心血管数据集，该数据集由不同属性组组成，可能揭示年轻患者中某些特定心血管问题的存在。给出了一个案例研究，展示了使用AREX对患者进行分类以及从数据集中发现可能的新医学知识。定义的知识发现循环包括医学专家对归纳规则的评估，以推动规则集朝着更合适的解决方案进化。最终结果是在儿科心脏病学领域发现了一种可能的新医学知识。
