Incorporating domain knowledge into data mining classifiers: An application in indirect lending

Aha, 1991, Instance-based learning algorithms, Machine Learning, 6, 37, 10.1007/BF00153759 Ambrosino, 1999, The use of physician domain knowledge to improve the learning of rule-based models for decision-support, 192 Barakat, 2007, Rule extraction from support vector machines: a sequential covering approach, IEEE Transactions on Knowledge and Data Engineering, 19, 729, 10.1109/TKDE.2007.190610 Bradley, 1997, The use of the area under the ROC curve in the evaluation of machine learning algorithms, Pattern Recognition, 30, 1145, 10.1016/S0031-3203(96)00142-2 Buchanan, 1984 Chauvin, 1995 Chung, 1993, A comparative analysis of inductive learning algorithms, Intelligent Systems in Accounting, Finance and Management, 2, 3 Daniels, 2002, Integrating economic knowledge in data mining algorithms Doumpos, 2002, Credit risk assessment using a multicriteria hierarchical discrimination approach: a comparative analysis, European Journal of Operational Research, 138, 392, 10.1016/S0377-2217(01)00254-5 Dybowski, 2003, Introduction to the special issue on the fusion of domain knowledge with data for decision support, Journal of Machine Learning Research, 4, 293 Elkan, 2001, The foundations of cost-sensitive learning, 973 Fan, 2006, An integrated two-stage model for intelligent information routing, Decision Support Systems, 42, 362, 10.1016/j.dss.2005.01.007 Fan, 2006, Nonlinear ranking function representations in genetic programming-based ranking discovery for personalized Web search, Decision Support Systems, 42, 1338, 10.1016/j.dss.2005.11.002 Fayyad, 1996, From data mining to knowledge discovery in databases, AI Magazine, 17, 37 Fawcett, 2003, ROC graphs: notes and practical considerations for data mining researchers Hand, 2001 Hanley, 1983, A method of comparing the areas under receiver operating characteristic curves derived from the same cases, Radiology, 148, 839, 10.1148/radiology.148.3.6878708 1983 Hirsh, 1994, Using background knowledge to improve inductive learning: a case study in molecular biology, IEEE Expert, 10, 3, 10.1109/64.331477 Hoffman, 1987, The problem of extracting the knowledge of experts from the perspective of experimental psychology, AI Magazine, 53 Hosmer, 2000 Huang, 2004, Credit rating analysis with support vector machines and neural networks: a market comparative study, Decision Support Systems, 37, 543, 10.1016/S0167-9236(03)00086-1 Huang, 2005, Using AUC and accuracy in evaluating learning algorithms, IEEE Transactions on Knowledge and Data Engineering, 17, 299, 10.1109/TKDE.2005.50 John, 1995, Estimating continuous distributions in Bayesian classifiers, 338 Johnson, 1983, What kind of expert should a system be?, Journal of Medicine and Philosophy, 8, 77, 10.1093/jmp/8.1.77 Keerthi, 1999, Improvements to Platt's SMO algorithm for SVM classifier design Kim, 1999, Expert, linear models, and nonlinear models of expert decision making in bankruptcy prediction: a lens model analysis, Journal of Management Information Systems, 16, 189, 10.1080/07421222.1999.11518239 Kohavi, 1995, The power of decision tables Kohavi, 1995, A study of cross-validation and bootstrap for accuracy estimation and model selection, 1137 Kopanas, 2002, The role of domain knowledge in a large scale data mining project, 288 Lam, 2004, Neural network techniques for financial performance prediction: integrating fundamental and technical analysis, Decision Support Systems, 37, 567, 10.1016/S0167-9236(03)00088-5 Langseth, 2003, Fusion of domain knowledge with data for structural learning in object oriented domains, Journal of Machine Learning Research, 4, 339 Murthy, 1998, Automatic construction of decision trees from data: a multi-disciplinary survey, Data Mining and Knowledge Discovery, 2, 345, 10.1023/A:1009744630224 Pazzani, 1992, The utility of knowledge in inductive learning, Machine Learning, 9, 57, 10.1007/BF00993254 Pazzani, 1994, Reducing misclassification costs, 217 Platt, 1998, Fast training of support vector machines using sequential minimal optimization, 185 Pohle, 2003, Integrating and updating domain knowledge with data mining Provost, 2001, Robust classification for imprecise environments, Machine Learning, 42, 203, 10.1023/A:1007601015854 Provost, 1998, The case against accuracy estimation for comparing induction algorithms, 445 Quinlan, 1986, Induction of decision trees, Machine Learning, 1, 81, 10.1007/BF00116251 Quinlan, 1993 Rumelhart, 1986, Learning internal representations by error propagation, 318 Russell, 1995 Ryu, 2005, Firm bankruptcy prediction: experimental comparison of isotonic separation and other classification approaches, IEEE Transactions on Systems, Man and Cybernetics, Part A, 35, 727, 10.1109/TSMCA.2005.843393 Siegel, 1956 Sinha, 2005, Evaluating and tuning predictive data mining models using receiver operating characteristic curves, Journal of Management Information Systems, 21, 253 Sung, 1999, Dynamics of modeling in data mining: interpretive approach to bankruptcy prediction, Journal of Management Information Systems, 16, 63, 10.1080/07421222.1999.11518234 Waterman, 1986 Weiss, 2003, Knowledge-based data mining, 456 Weiss, 1998 Weiss, 1991 Weiss, 2001, The effect of class distribution on classifier learning: an empirical study Witten, 2005 Zhao, 2004, Constrained cascade generalization of decision trees, IEEE Transactions on Knowledge and Data Engineering, 16, 727, 10.1109/TKDE.2004.3 Zhao, 2005, An efficient algorithm for generating generalized decision forests, IEEE Transactions on Systems, Man, and Cybernetics, Part A, 35, 754, 10.1109/TSMCA.2005.843392 Zhu, 2001, Data mining for network intrusion detection: a comparison of alternative methods, Decision Sciences, 32, 635, 10.1111/j.1540-5915.2001.tb00975.x