Path: Top -> Journal -> Telkomnika -> 2016 -> Vol 14, No 3A
Data Mining Based on the Rough Analysis and the Application in the Telecommunication Network Quality Evaluation
Data Mining Based on the Rough Analysis and the Application in the Telecommunication Network Quality Evaluation
Journal from gdlhub / 2016-11-11 07:45:59Oleh : Yujuan Guan, Wenyu ZhangYujuan Guan, Wenyu Zhang, Telkomnika
Dibuat : 2016-09-01, dengan 1 file
Keyword : data mining, rough set, classification approximation, telecommunication network quality evaluation
Url : http://journal.uad.ac.id/index.php/TELKOMNIKA/article/view/4380
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.
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.
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