On the Usability of Probably Approximately Correct Implication Bases

Autor:	Borchmann, Daniel, Hanika, Tom, Obiedkov, Sergei
Rok vydání:	2017
Předmět:	Computer Science - Artificial Intelligence Computer Science - Learning Computer Science - Logic in Computer Science 03G10 68T27 F.4.1 I.2.6
Druh dokumentu:	Working Paper
DOI:	10.1007/978-3-319-59271-8_5
Popis:	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. Comment: 17 pages, 8 figures; typos added, corrected x-label on graphs
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1701.00877 Zobrazit plný text záznamu View this record from Arxiv