Classification and analysis of clustering algorithms for large datasets

Data mining is the analysis step for discovering knowledge and patterns in large databases and large datasets [1]. Data mining is the process of applying machine learning methods with the intention of uncovering hidden patterns in large data sets. Data mining techniques basically involves many different ways to classify the data. Such classified data are used to fast accesses of data and for providing fast services to the customers. This paper gives an overview of available algorithms that can be used for clustering in large datasets. The comparative analysis of available clustering algorithms is provided in this paper. This paper also includes the future directions for researchers in the large database clustering domain.