scholarly journals Distortion-Guided Structure-Driven Interactive Exploration of High-Dimensional Data

2014 ◽  
Vol 33 (3) ◽  
pp. 101-110 ◽  
Author(s):  
S. Liu ◽  
B. Wang ◽  
P.-T. Bremer ◽  
V. Pascucci
Informatics ◽  
2019 ◽  
Vol 6 (2) ◽  
pp. 16 ◽  
Author(s):  
Lucas de Carvalho de Carvalho Pagliosa ◽  
Alexandru C. Telea

RadViz is one of the few methods in Visual Analytics able to project high-dimensional data and explain formed structures in terms of data variables. However, RadViz methods have several limitations in terms of scalability in the number of variables, ambiguities created in the projection by the placement of variables along the circular design space, and ability to segregate similar instances into visual clusters. To address these limitations, we propose RadViz++, a set of techniques for interactive exploration of high-dimensional data using a RadViz-type metaphor. We demonstrate the added value of our method by comparing it with existing high-dimensional visualization methods, and also by analyzing a complex real-world dataset having over a hundred variables.


Author(s):  
Jesper Kristensen ◽  
Son T. Mai ◽  
Ira Assent ◽  
Jon Jacobsen ◽  
Bay Vo ◽  
...  

2009 ◽  
Vol 35 (7) ◽  
pp. 859-866
Author(s):  
Ming LIU ◽  
Xiao-Long WANG ◽  
Yuan-Chao LIU

Author(s):  
Punit Rathore ◽  
James C. Bezdek ◽  
Dheeraj Kumar ◽  
Sutharshan Rajasegarar ◽  
Marimuthu Palaniswami

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