An Automated Report Generation Tool for the Data Understanding Phase
Juha Vesanto, Jaakko Hollmén · 2002
To prepare and model data successfully, the data miner needs to be aware of the properties of the data manifold. In this paper, the outline of a tool for automatically generating data survey reports for this purpose is described. The report combines linguistic descriptions (rules) and statistical measures with visualizations. Together these provide both quantitative and qualitative information and help the user to form a mental model of the data. The main focus is on describing the cluster structure and the contents of the clusters. The data is clustered using a novel algorithm based on the Self-Organizing Map. The rules describing the clusters are selected using a significance measure based on the confidence on their characterizing and discriminating properties. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.