A survey of clustering techniques and algorithms

Clustering is used data mining technique in which a group of similar objects is combined together to form clusters, these clusters are different from the objects in another clusters. This paper describes some clusterization techniques like, partitional technique, hierarchical technique, grid-based technique, density-based technique and their algorithms. Partitional method divides the data set into objects based on some similarity criterion, hierarchical method creates a hierarchy between clusters by combining the data objects into clusters, and then these clusters are further combined together to form large clusters and so on, grid-based method forms clusters by combining the data objects into grids or cells, density based method are used to separate the high dense clusters from low dense clusters.