THEORY APPROACH ON ROUGH SET

Unsupervised clustering is an essential technique in Data mining. Rule identification involves the application of Data mining techniques to derive usage patterns from the information system. Knowled ge extraction from data is the key to success in many fields. Knowledge extraction techniques and tools can assist humans in analyzing mountains of data and to turn the information contained in the data into successful decision making. This paper proposes, to consider an information system without any decision attribute. The proposal is useful when we get data, which contains only input information (condition attributes) but without decision (class attribute). K - Means algorithm is applied to cluster the giv en information system for different values of K. Decision table could be formulated using this clustered data as the decision variable.