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Visual exploration of classification models for risk assessment
2010
2010 IEEE Symposium on Visual Analytics Science and Technology
In risk assessment applications well informed decisions are made based on huge amounts of multi-dimensional data. In many domains not only the risk of a wrong decision, but in particular the trade-off between the costs of possible decisions are of utmost importance. In this paper we describe a framework tightly integrating interactive visual exploration with machine learning to support the decision making process. The proposed approach uses a series of interactive 2D visualizations of numeric
doi:10.1109/vast.2010.5652398
dblp:conf/ieeevast/MigutW10
fatcat:pn7ptfhfyrdvlpb4727j3wxala