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arXiv · 1701.00877

On the Usability of Probably Approximately Correct Implication Bases

Daniel Borchmann·Tom Hanika·Sergei Obiedkov
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Abstract

We revisit the notion of probably approximately correct implication bases from the literature and present a first formulation in the language of formal concept analysis, with the goal to investigate whether such bases represent a suitable substitute for exact implication bases in practical use-cases. To this end, we quantitatively examine the behavior of probably approximately correct implication bases on artificial and real-world data sets and compare their precision and recall with respect to their corresponding exact implication bases. Using a small example, we also provide qualitative insight that implications from probably approximately correct bases can still represent meaningful knowledge from a given data set.

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Daniel Borchmann, Tom Hanika, Sergei Obiedkov. 2017-01-18. On the Usability of Probably Approximately Correct Implication Bases. https://doi.org/10.1007/978-3-319-59271-8_5

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