面向软件缺陷数据的负关联规则挖掘方法
A Negative Association Rules Mining Method Oriented to Software Defect Data
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摘要: 面向软件缺陷数据的关联规则挖掘的意义在于探寻软件缺陷数据之间的关联关系,为软件开发、测试人员提供一定的指导作用.负关联规则阐述的是不同项目之间的相互排斥关系,具有非常重要的意义.本文通过引入数据矩阵的概念及遗传算法的思想,提出了一种新颖的负关联规则挖掘方法GMNAR,并通过实验验证了该方法的有效性和高效性.Abstract: Negative association rules describe the mutual exclusion of different items, which is also very important. In this thesis, a novel negative association rules mining method called GMNAR is proposed by introducing discernable matrixes concept and Genetic algorithm idea. And the experiment shows that it is effective and efficient.
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