Research Of Attribute Reduction And Application On Varaible Precision Rough Sets

Rough set theory is an important mathematical approach to uncertain and vague problem analysis. The main advantage of rough set theory is that it does not need any additional information. Rough set theory has been applied successfully for the field of decision analysis, knowledge acquisition, pattern recognition, medical diagnosis, financial analysis and soon.A study of attribute reduction is a very important aspect of rough set. It was proved that find optimal or all reduction is a Np-hard problem. This text does the following research for attribute reduction and application on the rough set of variable precision.Study attribute reduction algorithm of variable precision rough set. This article proposes two attribute reduction algorithms from the classification quality level and equivalent level. Based on the level of classification quality proposes weight of information quantity and important degree reduction algorithm, the algorithm considers two factors: the attributes of the information quantity and the attributes can distinguish the number of objects, improve the quality of the reduction. In addition, reduction algorithm based on equivalent level insures the reduction is a true reduction. And demonstrate algorithms by examples. The examples show that the algorithm is effective.Research the application of attribute reduction of variable precision rough set in the Shanghai and Shenzhen A-share analysis. The author elected 37 stocks which raise more than 50 percent in the 15 trading days before January 8, 2008, earnings per share, net assets yield etc. 8 stocks' indicators are attributes, establishment of a model application. After data preprocessing, use the reduction algorithm of weighted of information quantity and importance degree, get the reduction, on the basis of Reduction, use SAS Statistical analysis software has a non-linear regression analysis to the reduction model, the conclusion is signification, greatly simplifying the analysis of complexity. Further expand the application of the variable precision rough set in the financial analysis, have some innovative and practical.