Provided by:
World of Computer Science and Information Technology
Topic:
Data Management
Format:
PDF
Clustering is process of grouping data objects into distinct clusters so that data in the same cluster are similar. The most popular clustering algorithm used is the k-means algorithm, which is a partitioning algorithm. Unsupervised techniques like clustering may be used for fault prediction in software modules. This paper describes the standard k-means algorithm and analyzes the shortcomings of standard k-means algorithm. This paper proposes an incremental clustering algorithm. Experimental results show that the proposed algorithm produces clusters in less computation time.
