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Rule Based Networks: An Efficient and Interpretable Representation of Computational Models


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[1] U. Fayyad, G. Piatetsky-Shapiro and P. Smyth, From Data Mining to Knowledge Discovery in Databases, AI Magazine, vol. 17, no. 3, pp. 37–54, 1996Search in Google Scholar

[2] F. Stahl and I. Jordanov, An overview of use of neural networks for data mining tasks, WIREs: Data Mining and Knowledge Discovery, pp. 193–208, 201210.1002/widm.1052Search in Google Scholar

[3] P.-N. Tan, M. Steinbach and V. Kumar, Introduction to Data Mining, New Jersey: Pearson Education, 2006Search in Google Scholar

[4] T. Mitchell, Machine Learning, New York: McGraw Hill, 1997Search in Google Scholar

[5] H. Liu, A. Gegov and F. Stahl, Unified Framework for Construction of Rule Based Classification Systems, in Inforamtion Granularity, Big Data and Computational Intelligence, vol. 8, W. Pedrycz and S. Chen, Eds., Springer, 2015, pp. 209–23010.1007/978-3-319-08254-7_10Search in Google Scholar

[6] C. M. Higgins, Classification and Approximation with Rule Based Networks, Pasadena, California, 1993.Search in Google Scholar

[7] A. M. Uttley, The Design of Conditional Probability Computers, Information and control, vol. 2, pp. 1–24, 195910.1016/S0019-9958(59)90058-0Search in Google Scholar

[8] I. Kononenko, Bayesain Neual Networks, Biological Cybernetics, vol. 61, pp. 361–370, 198910.1007/BF00200801Search in Google Scholar

[9] F. Rosenblatt, Principles of Neurodynamics: Perceptron and the Theory of Brain Mechanisms, Washington, DC: Spartan Books, 196210.21236/AD0256582Search in Google Scholar

[10] O. Ekeberg and A. Lansner, Automatic generation of internal representations in a probabilistic artificial neural network, in Proceedings of the First European Conference on Neural Networks, 1988Search in Google Scholar

[11] A. V. Aho, J. E. Hopcraft and J. D. Ullman, Data Structures and Algorithms, Amsterdam: Addison-Wesley, 1983Search in Google Scholar

[12] H. Liu, A. Gegov and F. Stahl, Categorization and Construction of Rule Based Systems, in 15th International Conference on Engineering Applications of Neural Networks, Sofia, Bulgaria, 201410.1007/978-3-319-11071-4_18Search in Google Scholar

[13] J. Furnkranz, Separate-and-Conquer rule learning, Artificial Intelligence Review, vol. 13, pp. 3–54, 199910.1023/A:1006524209794Search in Google Scholar

[14] R. Quinlan, C4.5: programs for machine learning, Morgan Kaufman, 1993Search in Google Scholar

[15] J. Cendrowska, PRISM: an algorithm for inducing modular rules, International Journal of Man-Machine Studies, vol. 27, p. 349-370, 198710.1016/S0020-7373(87)80003-2Search in Google Scholar

[16] X. Deng, A covering-based algorithm for classification: PRISM, SK, 2012Search in Google Scholar

[17] A. Gegov, Complexity Management in Fuzzy Systems, Berlin: Springer, 2007Search in Google Scholar

[18] T. J. Ross, Fuzzy Logic with Engineering Applications, West Sussex: John Wiley & Sons Ltd, 2004Search in Google Scholar

[19] S. G. Simpson, Mathematical Logic, PA, 2013Search in Google Scholar

[20] A. Holland, Lecture 2: Rules based systems, 2010Search in Google Scholar

[21] H. Liu, A. Gegov and M. Cocea, Network Based Rule Representation for Knowledge Discovery and Predictive Modelling, in IEEE International Conference on Fuzzy Systems, Istanbul, 201510.1109/FUZZ-IEEE.2015.7337807Search in Google Scholar

[22] H. Liu, A. Gegov and M. Cocea, Rule Based Systems for Big Data: A Machine Learning Approach, 1 ed., vol. 13, Switzerland: Springer, 2016Search in Google Scholar

eISSN:
2083-2567
Language:
English
Publication timeframe:
4 times per year
Journal Subjects:
Computer Sciences, Databases and Data Mining, Artificial Intelligence