Comparing the Partitional and Density Based Clustering Algorithms by Using Weka Tool

Data mining is the process of extracting knowledge from the huge amount of data. The data can be stored in databases and information repositories. Data mining task can be divided into two models descriptive and predictive model. In Predictive model we can predict the values from different set of sample data, they are classified into three types such as classification, regression and time series. Descriptive model enables us to determine patterns in a sample data and sub-divided into clustering, summarization and association rules. Clustering creates group of classes based on the patterns and relationship between the data. There are different types of clustering algorithms partition, density based algorithm. In this paper we are analysing and comparing the various clustering algorithm by using WEKA tool to find out which algorithm will be more comfortable for the users.