Authors:
Gurminder Kaur
and
Bijaya B. Karki
Affiliation:
School of Electrical Engineering and Computer Science, Louisiana State University, Baton Rouge, 70803 and U.S.A.
Keyword(s):
Parallel Coordinates, Multivariate Data Visualization, Frequency Distribution, Correlations.
Related
Ontology
Subjects/Areas/Topics:
Abstract Data Visualization
;
Computer Vision, Visualization and Computer Graphics
;
General Data Visualization
;
High-Dimensional Data and Dimensionality Reduction
;
Information and Scientific Visualization
;
Interactive Visual Interfaces for Visualization
;
Interface and Interaction Techniques for Visualization
;
Large Data Visualization
;
Visual Data Analysis and Knowledge Discovery
;
Visual Representation and Interaction
;
Visualization Algorithms and Technologies
Abstract:
We present two innovative ways of enhancing parallel coordinates axes to better understand all variables and their interrelationships in high-dimensional datasets. Histogram and circle/ellipse plots based on uniform (linear) and non-uniform frequency/density mappings are adopted to visualize distributions of numerical and categorical data values. These plots are, particularly, helpful in emphasizing data values of low frequencies as well as those with similar frequencies. Color-mapped axis stripes are designed to visually connect numerical variables irrespective of their locations (adjacent or nonadjacent axes) in the parallel coordinates layout so that correlations can be fully realized in the same display. Distribution plots and axis stripes are integrated to further facilitate exploratory analysis of multivariate data with respect to a complete variable set.