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Erschienen in:
2014 | OriginalPaper | Buchkapitel
Visual-Based Detection of Properties of Confirmation Measures
verfasst von : Robert Susmaga, Izabela Szczęch
Erschienen in: Foundations of Intelligent Systems
Verlag: Springer International Publishing
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The paper presents a visualization technique that facilitates and eases analyses of interestingness measures with respect to their properties. Detection of properties possessed by these measures is especially important when choosing a measure for KDD tasks. Our visual-based approach is a useful alternative to often laborious and time consuming theoretical studies, as it allows to promptly perceive properties of the visualized measures. Assuming a common, four-dimensional domain of the measures, a synthetic dataset consisting of all possible contingency tables with the same number of observations is generated. It is then visualized in 3D using a tetrahedron-based barycentric coordinate system. Additional scalar function - an interestingness measure - is rendered using colour. To demonstrate the capabilities of the proposed technique, we detect properties of a particular group of measures, known as confirmation measures.