A Method for Measuring Similarity of Software Defect Data

被引：0
|
作者：
Wan, Lin [1 ]
Yang, Tengxiang [1 ]
Liu, Haining [2 ]
机构：
[1] Acad Armored Force Engn, Dept Informat Engn, Beijing, Peoples R China
[2] China Acad Ordnance Sci, Beijing, Peoples R China
来源：
2017 IEEE 2ND ADVANCED INFORMATION TECHNOLOGY, ELECTRONIC AND AUTOMATION CONTROL CONFERENCE (IAEAC) | 2017年
关键词：
fuzzy cluster; similarity; software defects;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The essence of the classification method is the similarity measure, which divides the objects with the same attributes into one class for analysis. In this paper, we first study the similarity measure method of mixed attributes of data mining, and introduce the attribute weight calculation method of defect data to take into account the influence of different attributes on the similarity measurement. It not only reflects the degree of similarity between the attributes of the defect data, but also reflects the distance between the attributes. In this paper, the defect data are analyzed and the results are measured. The experimental results show that the improved similarity measure has a certain degree of improvement in accuracy.
引用
收藏
页码：1108 / 1112
页数：5
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