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Author(s) 
Ming, H., Dayal, U., Sharma, R. K., Keim, D., Janetzko, H. 
Title 
Visual analytics of large multidimensional data using variable binned scatter plots 
Abstract 
The scatter plot is a wellknown method of visualizing pairs of twodimensional continuous variables. Multidimensional data can be depicted in a scatter plot matrix. They are intuitive and easytouse, but often have a high degree of overlap which may occlude a significant portion of data. In this paper, we propose variable binned scatter plots to allow the visualization of large amounts of data without overlapping. The basic idea is to use a nonuniform (variable) binning of the x and y dimensions and plots all the data points that fall within each bin into corresponding squares. Further, we map a third attribute to color for visualizing clusters. Analysts are able to interact with individual data points for record level information. We have applied these techniques to solve realworld problems on credit card fraud and data center energy consumption to visualize their data distribution and causeeffect among multiple attributes. A comparison of our methods with two recent wellknown variants of scatter plots is included. 
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