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Investigation and Application of Extension Data Mining Based on Rough Set

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2 Author(s)
Tang Zhi-hang ; Sch. of Comput. & Commun., Hunan Inst. of Eng., Xiangtan, China ; Yang Bao-an

In the data base of information system, usually there are some attributes which are unimportant to the decision attribute, and some records that disturb the decision making. In this paper, reducing the condition attributes based on the matter-element theory and rough set method, calculating the importance to the decision attribute for each condition attribute after reduction, and data mining the relevant rules based on the reduced attributes, extension relevant function is used to depict quality of data gather in data mining. Combination of extension methods and clustering, extension classified prediction model is established. Extension theory researches on rules and methods of solving conflicts from qualitative and quantitative aspect. Its theory support is matter-element and extension set. Extension classified prediction is an applied technology using extension method in prediction fields. The result means that using extension classified prediction method to predict ARPU of China Unicom is feasible. This trial will be helpful to related decision made by manages.

Published in:

Fuzzy Systems and Knowledge Discovery, 2009. FSKD '09. Sixth International Conference on  (Volume:7 )

Date of Conference:

14-16 Aug. 2009