In this paper, the newly proposed Bayesian rough set model is analyzed, and the defect of the model is discussed, further more, a modified form of the model is proposed.

This chapter mostly tells the rough set model under equivalence relation,common relation and probability,gives their definition property and respective kinds of definition type,the relationship between them,and examples.

The validity of the algorithm is verified by examples and the important theoretical foundation can then be provided to solve the problem of the rough set model with incomplete information system.

The rough set model algorithm based on the decision table was used in project evaluation to acquire common decision knowledge from decisions of many specialists as the criterion and the final result of project evaluation so as to improve the existing evaluation algorithm.

A new generalized rough set model is constructed to deal with situations where different data objects have different importance and different attributes have different characteristics using a weighting function for data objects and the attribute characteristic function.

In this paper,the authors have presented an algorithm SRII based on probabilistic rough set model,which eliminates attributes very efficiently and effectively.