文章基本信息

标题：Data Mining Based on the Rough Analysis and the Application in the Telecommunication Network Quality Evaluation
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作者：Yujuan Guan ; Wenyu Zhang
期刊名称：TELKOMNIKA (Telecommunication Computing Electronics and Control)
印刷版ISSN：2302-9293
出版年度：2016
卷号：14
期号：3A
页码：313-320
DOI：10.12928/telkomnika.v14i3A.4380
语种：English
出版社：Universitas Ahmad Dahlan
摘要：The precision of the classification rule is decided by the construction of the classification algorithm. In this paper, after the introducing of the concepts and the attribute-reduction algorithms of the basic rough set, a data-mining algorithm based on the rough impend approximation measurement is demonstrated. At first, the finding theory of the classification rule is introduced. After that, according to the importance-measurement of the conditional attributes in the decision table, one kind of new attributes reduction method in the field of data mining, which is based on the improved rough impend approximation measurement, is explained. Lastly, the method is applied in the telecommunication network quality evaluation, and the rationality and feasibility of algorithm are examined in this example.
其他摘要：The precision of the classification rule is decided by the construction of the classification algorithm. In this paper, after the introducing of the concepts and the attribute-reduction algorithms of the basic rough set, a data-mining algorithm based on the rough impend approximation measurement is demonstrated. At first, the finding theory of the classification rule is introduced. After that, according to the importance-measurement of the conditional attributes in the decision table, one kind of new attributes reduction method in the field of data mining, which is based on the improved rough impend approximation measurement, is explained. Lastly, the method is applied in the telecommunication network quality evaluation, and the rationality and feasibility of algorithm are examined in this example.
关键词：data mining; rough set; classification approximation; telecommunication network quality evaluation