An Interactive Scatter Plot Metrics Visualization for Decision Trend Analysis

Abstract

This paper presents a new interactive scatter plot visualization for multi-dimensional data analysis. We apply RST to reduce the visual complexity through dimensionality reduction. We use an innovative point-to-region mouse click concept to enable direct interactions with scatter points that are theoretically impossible. To show the decision trend we use a virtual Z dimension to display a set of linear flows showing approximation of the decision trend. We have conducted a case study to demonstrate the effectiveness and usefulness of our new technique for identifying the impact sources of wine quality through the visual analytics of a wine dataset consisting of 12 attributes with 4898 samples.