Application of a New Fast Algorithm for Getting Approximate Operators of Rough Set to Information System Classification

The information system classification is a crucial part of data mining, which aims to analysis the information system, extract important message from complex data, and forecast the future development trend of data. At present, there are many methods to classify the data, for example, Rough Set Theory, Decision Tree, Bayesian Network, Genetic Algorithm, etc. The method presented in this paper, based on ID3 Algorithm, associated with the combination of Rough Set Theory and Decision Tree Theory, uses the conditional attribute as the decision tree's node to classify data in the information system. Moreover, a new fast algorithm for getting approximate operators is used in the information system classification to improve the efficiency.