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Method for generating decision implication canonical basis based on true premises

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Abstract

Formal concept analysis is able to visualize and represent knowledge using concept lattice and (attribute) implication. Decision implication is a counterpart of implication in the setting of decision-making. Decision implication canonical basis is a complete, non-redundant and optimal set of decision implications. At present, decision implication canonical basis can be generated with the help of minimal generators; however, this method is not efficient because of its exponential complexity. To solve this problem, we propose an algorithm to generate decision implication canonical basis based on true premises and analyze its time complexity. Experimental results verify the efficiency of this algorithm.

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Acknowledgments

The works described in this paper are supported by the Project supported by the State Key Program of National Natural Science of China (No. 61432011, U1435212), National Natural Science Foundation of China (Nos. 61272095, 61573231, 61303107, 41401521 and 61175067), Shanxi Scholarship Council of China (2013–2014), the Natural Science Foundation of Shanxi, China (201601D021072) and Shanxi Science and Technology Infrastructure (2015091001-0102).

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Correspondence to Yanhui Zhai.

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Li, D., Zhang, S. & Zhai, Y. Method for generating decision implication canonical basis based on true premises. Int. J. Mach. Learn. & Cyber. 8, 57–67 (2017). https://doi.org/10.1007/s13042-016-0575-2

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  • DOI: https://doi.org/10.1007/s13042-016-0575-2

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