LSNCCP:A Clustering Algorithm Based on the Largest Set of Not-Covered Core Points

Clustering is an important application area for many fields including data mining, pattern recognition, etc. In this paper, a novel clustering algorithm LSNCCP（a clustering algorithm based on the largest set of not-covered core points） is proposed. On the basis of the definition of density, the distance between the core points is discussed. And then, the three essential distance relation: covered core points, intersectant core points, and separate core points. Finally, the largest set of not-covered core points is found and based on the set the data can cluster very well. Because the largest set of not-covered core points is a lesser subset of the all core points, the new algorithm cuts short the time of searching all core points in the similar algorithms. The feasibility and the advantage or the new algorithm are proved in theory and experiment.