Analysis of High Dimension Clustered Data using Visualization Technique

In Data mining, One of the most significant and important technique is Cluster Analysis. The major stumbling block of cluster analysis is that it provides numerical feedback making it Onerous for users to understand, and most of the clustering algorithms are not pertinent for dealing with arbitrarily shaped data distributions of datasets. In Data mining, the visualization techniques have been proven to be more effectual, their accomplishment in cluster analysis is still a hurdle, especially in applications with immense and high dimensional datasets. In This paper I have introduced a distinct approach, Hypothesis Oriented Verification and Validation by Visualization, named HOV3, it gathers datasets on a hypothesis by visualization in 2D space. The HOV3 technique is goal oriented, it can reside the user to discover more cluster information from high dimensional data sets in a productive and organized way.