Calculation Of Knowledge Granulation And Study Of Its Application In Attribute Reduction

The theory and method of Rough set is a data analysis tool able to analyze and deal with inconsistent, inaccurate, incomplete information effectively. The theory and methods have been application successful in pattern recognition, machine learning, decision support, knowledge discovery, predictive modeling and other areas. Calculation of knowledge granularity and properties of knowledge reduction as the rough set theory and application of key technologies has become the research focus of concern.The main contents of this paper include:Introduced the basic concepts and research status theory of rough set theory and size theory. Proposed the more generalization form of knowledge granularity on the basis of already exists. Get the portfolio granularity and the polynomial granularity. They include the common knowledge granularity, And discuss the nature of these granularity. Given a new importance based on the properties of granularity attribute reduction algorithm. And a reduction algorithm based on the sense of granularity. These results have certain theoretical significance and application value in establish the granularity in the information system and the attribute reduction.