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VIS
2009
IEEE

Visual Human+Machine Learning

13 years 4 months ago
Visual Human+Machine Learning
In this paper we describe a novel method to integrate interactive visual analysis and machine learning to support the insight generation of the user. The suggested approach combines the vast search and processing power of the computer with the superior reasoning and pattern recognition capabilities of the human user. An evolutionary search algorithm has been adapted to assist in the fuzzy logic formalization of hypotheses that aim at explaining features inside multivariate, volumetric data. Up to now, users solely rely on their knowledge and expertise when looking for explanatory theories. However, it often remains unclear whether the selected attribute ranges represent the real explanation for the feature of interest. Other selections hidden in the large number of data variables could potentially lead to similar features. Moreover, as simulation complexity grows, users are confronted with huge multidimensional data sets making it almost impossible to find meaningful hypotheses at all....
Raphael Fuchs, J├╝rgen Waser, Meister Eduard Gr├
Added 06 Nov 2009
Updated 17 Feb 2010
Type Conference
Year 2009
Where VIS
Authors Raphael Fuchs, J├╝rgen Waser, Meister Eduard Gr├Âller
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