1 research outputs found
A Visual Measure of Changes to Weighted Self-Organizing Map Patterns
Estimating output changes by input changes is the main task in causal
analysis. In previous work, input and output Self-Organizing Maps (SOMs) were
associated for causal analysis of multivariate and nonlinear data. Based on the
association, a weight distribution of the output conditional on a given input
was obtained over the output map space. Such a weighted SOM pattern of the
output changes when the input changes. In order to analyze the change, it is
important to measure the difference of the patterns. Many methods have been
proposed for the dissimilarity measure of patterns. However, it remains a major
challenge when attempting to measure how the patterns change. In this paper, we
propose a visualization approach that simplifies the comparison of the
difference in terms of the pattern property. Using this approach, the change
can be analyzed by integrating colors and star glyph shapes representing the
property dissimilarity. Ecological data is used to demonstrate the usefulness
of our approach and the experimental results show that our approach provides
the change information effectively.Comment: 8 pages, 3 figures, conference, llncs styl