HD-eye: Visual mining of high-dimensional data

A new approach to visual clustering in high-dimensional data sets is proposed. Implemented in the HD-Eye system, the approach combines the strengths of an advanced automatic clustering algorithm with new visualization techniques that effectively support the clustering process by representing the important information visually. Experimental evaluation shows that the combination of automatic and visual techniques significantly improves the effectiveness of the data mining process and provides a better understanding of the results.