Visual Data Mining and Discovery in Multivariate Data Using Monotone n-D Structure

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Provided by: Central Washington University
Topic: Big Data
Format: PDF
Visual Data Mining (VDM) is an emerging research area of data mining and visual analytics to gain a deep visual understanding of data. A border between patterns can be recognizable visually, but its analytical form can be quite complex and difficult to discover. VDM methods have shown benefits in many areas, but these methods often fail in visualizing highly overlapped multidimensional data and data with little variability. The authors address this problem by combining visual techniques with the theory of monotone Boolean functions and data monotonization.
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