Abstract
We propose a method of visualizing statistical information in concept lattice diagrams. To this end, we examine the characteristics of support, confidence, and lift, which are parameters used in association analysis. Based on our findings, we develop the notion of cascading line diagrams, a visualization method that combines the properties of additive line diagrams with association analysis. In such diagrams, one can read the size of a concept’s extent from the height of the corresponding node in the diagram and, at the same time, the geometry of the formed quadrangles illustrates whether two attributes are statistically independent or dependent and whether they are negatively or positively correlated. In order to demonstrate this visualization method, we have developed a program generating such diagrams.
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Notes
- 1.
clarifying the context would prune duplicates but distort the statistical information
- 2.
Note, however, that the notion easily generalizes to settings where the weight expresses other qualities that justify to assign more statistical importance to certain objects (in which case one might rather choose \(\mathbb {Q}\) or \(\mathbb {R}\) as codomain).
- 3.
short: cascading line diagrams
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Klimpke, J., Rudolph, S. (2021). Visualization of Statistical Information in Concept Lattice Diagrams. In: Braud, A., Buzmakov, A., Hanika, T., Le Ber, F. (eds) Formal Concept Analysis. ICFCA 2021. Lecture Notes in Computer Science(), vol 12733. Springer, Cham. https://doi.org/10.1007/978-3-030-77867-5_13
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