The practical results show that the approach is effective and the complete relative minimal reduction in each class of the information system are obtained.

Through improving and extending the process of computing core,the minimal reduction algorithm based on attribute frequency heuristic information are put forward.

Attribute reduction is the most important research field in rough set, but the time complexity of computing all reductions and minimal reduction is exponential.

A method is given for sovling the problem of minimum reduction by using GA (genetic algorithm),based on rough sets and the extended matrix theory.

The influence of the necessary attributes after class subdivision on the upper and lower approximate values,quality and accuracy of approximate classification,number of decision-making rules and relative reduction are analyzed theoretically.

By means of the methodology of rough set,different attribute classification methods for decision systems are first analyzed in this paper,and the attribute significance as well as the extremely small subset of the attribute relative reduction caused by a classification variety is discussed.

Two parameters for different level partitions (or similar degree between objects) α,β are used in these reductions, in which the positive region formula of the decision level set are adopted for relative reduction and importance degree of attributes, and the distributed reducti.

The Research on RRECL-based Mining Association Rules;