A Review on Clustering Techniques in Data Mining
The main aim of Data mining process is to discover meaningful trends and patterns from the data hidden in repositories. For data analysis and data mining application, Clustering is important. It is a process or technique of grouping a set of objects that belong to the same class. Cluster analysis or Clustering has been widely used in several disciplines, such as statistics, software engineering, biology, psychology and other social sciences, in order to identify natural groups in large amounts of data. These data sets are constantly becoming larger, and their dimensionality prevents easy analysis and validation of the results. There are various clustering techniques like Simple K Means, EM, Farthest First, Filtered Clustering, Hierarchical Clustering etc. In this research work, a brief introduction to cluster analysis is given.