A Clustering Method Towards Multi-attribute Types Based on Rough Sets and Granularity

Nowadays, most of the clustering methods are studied towards the one fold attribute type, such as numerical attribute, character attribute etc. Therefore, it needs to develop the clustering method which could deal with multi-attribute types at the same time in order to satisfy the demanding of the modern large complicated data bases. In the paper, a clustering algorithm towards multi-attribute types is proposed based on rough sets and granularity. Being different from the traditional point of view, the algorithm could solve multi-attribute types and clustered well. And, a real example is illustrated to prove it feasible.