Starcluster: a visualization, clustering and classification tool

The multidimensional data representation has been one of the greatest challenges of Data Mining. The visual resource is very useful in the knowledge discovery process once it enables an easier and faster understanding of the data distribution. This work deals with the development of a tool that supports data exploration through visualization, clustering and classification methods. The tool is called Starcluster and it was implemented using Microsoft Excel and the Visual Basic programming language. Starcluster allows users to visualize and to manipulate multidimensional data using the new technique Star Coordinates. Star Coordinates is a coordinate transformation that enables the plotting of multidimensional data in 2D space. Each variable is represented by an axis and a point represents each multidimensional data element. By changing the size and angle of the axes, it is possible to integrate and separate dimensions, analyze correlations of multiple dimensions, view clusters, trends and outliers in the distribution of data. Starcluster also provides a k-means clustering method and principal components analysis to complement the data understanding task. This paper presents the main features of Starcluster and an application example.