Visualizing high-dimensional predictive model quality

TitleVisualizing high-dimensional predictive model quality
Publication TypeConference Papers
Year of Publication2000
AuthorsRheingans P, desJardins M
Conference NameVisualization 2000. Proceedings
Date Published2000///
PublisherIEEE
ISBN Number0-7803-6478-3
Abstract

Using inductive learning techniques to construct classification models from large, high-dimensional data sets is a useful way to make predictions in complex domains. However, these models can be difficult for users to understand. We have developed a set of visualization methods that help users to understand and analyze the behavior of learned models, including techniques for high-dimensional data space projection, display of probabilistic predictions, variable/class correlation, and instance mapping. We show the results of applying these techniques to models constructed from a benchmark data set of census data, and draw conclusions about the utility of these methods for model understanding.

URLhttp://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=885740
DOI10.1109/VISUAL.2000.885740