Supervised Learning Perspective in Logic Mining

Mohd Shareduwan Mohd Kasihmuddin, Siti Zulaikha Mohd Jamaludin, Mohd. Asyraf Mansor, Habibah A. Wahab and Siti Maisharah Sheikh Ghadzi
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Mohd Shareduwan Mohd Kasihmuddin: School of Mathematical Sciences, Universiti Sains Malaysia, George Town 11800, Malaysia
Siti Zulaikha Mohd Jamaludin: School of Mathematical Sciences, Universiti Sains Malaysia, George Town 11800, Malaysia
Mohd. Asyraf Mansor: School of Distance Education, Universiti Sains Malaysia, George Town 11800, Malaysia
Habibah A. Wahab: School of Pharmaceutical Sciences, Universiti Sains Malaysia, George Town 11800, Malaysia
Siti Maisharah Sheikh Ghadzi: School of Pharmaceutical Sciences, Universiti Sains Malaysia, George Town 11800, Malaysia

Mathematics, 2022, vol. 10, issue 6, 1-35

Abstract: Creating optimal logic mining is strongly dependent on how the learning data are structured. Without optimal data structure, intelligence systems integrated into logic mining, such as an artificial neural network, tend to converge to suboptimal solution. This paper proposed a novel logic mining that integrates supervised learning via association analysis to identify the most optimal arrangement with respect to the given logical rule. By utilizing Hopfield neural network as an associative memory to store information of the logical rule, the optimal logical rule from the correlation analysis will be learned and the corresponding optimal induced logical rule can be obtained. In other words, the optimal logical rule increases the chances for the logic mining to locate the optimal induced logic that generalize the datasets. The proposed work is extensively tested on a variety of benchmark datasets with various performance metrics. Based on the experimental results, the proposed supervised logic mining demonstrated superiority and the least competitiveness compared to the existing method.

Keywords: supervised learning; Hopfield neural network; logic mining; artificial neural network (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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