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[1] P. Smyth and R. M. Goodman, “An Information Theoretic Approach to Rule Induction from Databases,†vol. 4, no. 4, pp. 301–316, 1992. [2] R. Shinghal, “Evaluating the Interestingness of Characteristic Rules,†pp. 263–266, 1996. [3] S. Dreiseitl, M. Oil, C. Baumgartner, and S. Viterbo, "An evaluation of heuristics for rule ranking," Artif. Intell. Med., vol. 50, no. 3, pp. 175–180, 2010. [4] J. F. Roddick and M. Spiliopoulou, “A survey of temporal knowledge discovery paradigms and methods,†IEEE Trans. Knowl. Data Eng., vol. 14, no. 4, pp. 750–767, 2002. [5] F. Provost, “A Survey of Methods for Scaling Up Inductive Algorithms,†vol. 169, pp. 131–169, 1999. [6] I. Inza, P. Larrañaga, R. Etxeberria, and B. Sierra, “Feature Subset Selection by Bayesian network-based optimization,†vol. 123, pp. 157–184, 2000. [7] F. Provost, “Tree Induction for Probability-Based Ranking,†vol. 5, pp. 199–215, 2003. [8] J. Sulzmann and F. Johannes, “An Empirical Comparison of Probability Estimation Techniques for Probabilistic Rules,†no. 2003, pp. 317–331, 2009. [9] A. A. Freitas, “On rule interestingness measures,†Knowledge-Based Syst., vol. 12, no. March, pp. 309–315, 1999. [10] K. E. N. Mcgarry, “A survey of interestingness measures for knowledge discovery,†pp. 39–61, 2005. [11] X. Huynh, F. Guillet, J. Blanchard, and P. Kuntz, “A Graph-based Clustering Approach to Evaluate Interestingness Measures : A Tool and a Comparative Study,†vol. 50, pp. 25–50, 2007. [12] B. Vaillant, S. Lallich, and P. Lenca, “On the behavior of the generalizations of the intensity of implication : A data-driven comparative study,†vol. 447, pp. 421–447, 2008. [13] J. Hills, L. M. Davis, and A. Bagnall, “Interestingness Measures for Fixed Consequent Rules,†pp. 68–75, 2012. [14] P. Flach, N. Lavrac, and B. Zupan, “Rule Evaluation Measures: A Unifying View,†Proc. 9th Int. Work. Inductive Log. Program., pp. 174–185, 1999. [15] F. Johannes and P. A. Flach, “An Analysis of Rule Evaluation Metrics,†2003. [16] D. Christensen, “David Christensen - Measuring Confirmation.pdf.†pp. 437–461, 1999. [17] S. Greco, R. SÅ‚owi, and I. Szcz, “Measures of rule interestingness in various perspectives of confirmation,†vol. 347, pp. 216–235, 2016. [18] M. Michalak, M. Sikora, and Å. Wróbel, “Rule Quality Measures Settings in a Sequential Covering Rule Induction Algorithm - an Empirical Approach,†vol. 5, pp. 109–118, 2015. [19] P. F. Nada Lavrac, Bojan Cestnik, Dragan Gamberger, “Decision Support Through Subgroup Discovery : Three Case Studies and the Lessons Learned,†no. 1994, pp. 115–143, 2004. [20] D. M. W. Powers, “ROC-ConCert,†pp. 12–15, 2012. [21] P. Salgado, “Relevance as a new measure of relative importance: of sets of rules,†no. 3, pp. 3770–3777, 2000. [22] [22] F. Coenen and P. Leng, “An Evaluation of Approaches to Classification Rule Selection,†IEEE Int. Conf. Data Min., pp. 2–5, 2004. [23] Y. Yao and B. Zhou, “Micro and Macro Evaluation of Classification Rules,†Proc. Seventh IEEE Int. Conf. Cogn. Informatics, ICCI 2008, Stanford Univ. California, USA, 2008. [24] D. M. W. Powers, “Evaluation: From Precision, Recall And F-Measure To Roc, Informedness, Markedness & Correlation,†vol. 2, no. 1, pp. 37–63, 2011. [25] H. Abe, S. Tsumoto, M. Ohsaki, and T. Yamaguchi, “Evaluating Learning Algorithms to Construct Rule Evaluation Models Based on Objective Rule Evaluation Indices,†2007. [26] H. Abe, S. Tsumoto, M. Ohsaki, and T. Yamaguchi, “Evaluating Learning Algorithms to Support Human Rule Evaluation with Predicting Interestingness Based on Objective Rule Evaluation Indices,†vol. 282, no. 2008, pp. 269–282, 2008. [27] H. Abe and S. Tsumoto, “Comparing Accuracies of Rule Evaluation Models to Determine Human Criteria on Evaluated Rule Sets,†pp. 1–7, 2008. [28] H. Abe and S. Tsumoto, “Rule Evaluation Model as Behavioral Modeling,†pp. 8–15, 2009. [29] A. Gruca and M. Sikora, "Rule-based functional description of genes – Estimation of the multicriteria rule interestingness measure by the UTA method," Integr. Med. Res., vol. 33, no. 4, pp. 222–234, 2013. [30] A. Gruca and M. Sikora, “Data- and expert-driven rule induction and filtering framework for functional interpretation and description of gene sets,†pp. 1–14, 2017. [31] U. Stanczyk, “Weighting and Pruning of Decision Rules,†pp. 106–114, 2016. [32] K. K. Sethi, D. K. Mishra, and B. Mishra, “Novel Algorithm to Measure Consistency between Extracted Models from Big Dataset and Predicting Applicability of Rule Extraction,†IEEE Trans. Knowl. Data Eng., 2014. [33] H. Mutluri and P. Sujatha, “Challenges in Big Data using Data Mining Techniques,†Int. J. Comput. Eng. Res. Trends, vol. 2, no. 12, pp. 924–930, 2015.
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