A Survey on Data Clustering Algorithms

Clustering is a significant area of application for a range of fields including data mining, statistical data analysis, image compression, and vector quantization. Moreover Clustering has been formulated in different manners in machine learning, pattern recognition, optimization, and statistics literature. The basic problem in clustering arise at grouping together (clustering) data streams which are analogous to each other. A variety of algorithms have emerged that meet the requirements and were successfully applied to real-life data clustering problems. This paper makes a general survey on various Clustering algorithms that have been proposed earlier in literature. In addition the future enhancement section of this paper suggests some of the modifications of earlier proposed work to overcome their limitations.