An enhanced hierarchical clustering algorithm using weka tool

Clustering is one of the unsupervised learning method in which a set of essentials is separated into uniform groups. The Hierarchical clustering method is one of the most widely used clustering techniques for various application..In this paper we applied Squared Euclidean distance formula in Hierarchical algorithms for clustering of UCI Data sets using WEKA machine learning tool. WEKA is a popular tool for machine learning which was written in java. The WEKA provides a collection of visualization tools and algorithms for data analysis and predictive modeling through a graphical user interface. Experimental results on UCI data show that the Hierarchical algorithms when implemented using Squared Euclidean distance formula can make better cluster in minimum time, and have good performance as well as least number of iteration for building the clusters.