C4.5: programs for machine learning
C4.5: programs for machine learning
Fast training of support vector machines using sequential minimal optimization
Advances in kernel methods
Empirical evaluation of information visualizations: an introduction
International Journal of Human-Computer Studies - Empirical evaluation of information visualizations
Human Factors in Visualization Research
IEEE Transactions on Visualization and Computer Graphics
The challenge of information visualization evaluation
Proceedings of the working conference on Advanced visual interfaces
An Insight-Based Methodology for Evaluating Bioinformatics Visualizations
IEEE Transactions on Visualization and Computer Graphics
Improvements to Platt's SMO Algorithm for SVM Classifier Design
Neural Computation
Toward Measuring Visualization Insight
IEEE Computer Graphics and Applications
Evaluating information visualization applications with focus groups: the CourseVis experience
Proceedings of the 2006 AVI workshop on BEyond time and errors: novel evaluation methods for information visualization
Methods for the evaluation of an interactive InfoVis tool supporting exploratory reasoning processes
Proceedings of the 2006 AVI workshop on BEyond time and errors: novel evaluation methods for information visualization
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
Qualitative analysis of visualization: a building design field study
Proceedings of the 2008 Workshop on BEyond time and errors: novel evaLuation methods for Information Visualization
Usability and transferability of a visualization methodology for medical data
USAB'07 Proceedings of the 3rd Human-computer interaction and usability engineering of the Austrian computer society conference on HCI and usability for medicine and health care
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We describe the results of an empirical study comparing an interactive Information Visualization (InfoVis) technique called Gravi++ (GRAVI), Exploratory Data Analysis (EDA) and Machine Learning (ML). The application domain is the psychotherapeutic treatment of anorectic young women. The three techniques are supposed to support the therapists in finding the variables which influence success or failure in therapy. To evaluate the utility of the three techniques we developed on the one hand a report system which helped subjects to formulate and document in a self-directed manner the insights they gained when using the three techniques. On the other hand, focus groups were held with the subjects. The combination of these very different evaluation methods prevents jumping to false conclusions and enables for an comprehensive assessment of the tested techniques. The combined results indicate that the three techniques (EDA, ML, and GRAVI) are complementary and therefore should be used in conjunction.