Logic mining in neural network: reverse analysis method

Sathasivam, S. and Abdullah, W.A.T.W. (2011) Logic mining in neural network: reverse analysis method. Computing , 91 (2). pp. 119-133. ISSN 0010-485X, DOI https://doi.org/10.1007/s00607-010-0117-9.

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Neural networks are becoming very popular with data mining practitioners because they have proven through comparison their predictive power with statistical techniques using real data sets. Based on this idea, we will present a method for inducing logical rules from empirical data-Reverse Analysis. When the values of the connections of a neural network resulting from Hebbian learning for the data are given, we hope to know what logical rules are entrenched in it. This method is tested with some real life data sets. In real life data sets, logical rules are assumed to be in conjunctive normal form (CNF) since Horn clauses are inadequate.

Item Type: Article
Additional Information: Univ Malaya, Dept Phys, Fac Sci, Kuala Lumpur 50603, Malaysia
Uncontrolled Keywords: Computer Science, Theory & Methods
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Science > Department of Physics
Depositing User: Mr. Faizal Hamzah
Date Deposited: 07 Oct 2011 01:25
Last Modified: 19 Dec 2014 03:16
URI: http://eprints.um.edu.my/id/eprint/2171

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