Abstract
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.
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Susmaga, R., Szczęch, I. (2014). Visual-Based Detection of Properties of Confirmation Measures. In: Andreasen, T., Christiansen, H., Cubero, JC., Raś, Z.W. (eds) Foundations of Intelligent Systems. ISMIS 2014. Lecture Notes in Computer Science(), vol 8502. Springer, Cham. https://doi.org/10.1007/978-3-319-08326-1_14
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DOI: https://doi.org/10.1007/978-3-319-08326-1_14
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-08325-4
Online ISBN: 978-3-319-08326-1
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