Fraud analytics using descriptive, predictive, and social network techniques: a guide to data science for fraud detection von Baesens, Bart, Van Vlasselaer, Veronique, Verbeke, Wouter

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Benchmarking state-of-the-art classification algorithms for credit scoring: An update of research von Lessmann, Stefan, Baesens, Bart, Seow, Hsin-Vonn, Thomas, Lyn C.

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A multi-objective approach for profit-driven feature selection in credit scoring von Kozodoi, Nikita, Lessmann, Stefan, Papakonstantinou, Konstantinos, Gatsoulis, Yiannis, Baesens, Bart

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The value of big data for credit scoring: Enhancing financial inclusion using mobile phone data and social network analytics von Óskarsdóttir, María, Bravo, Cristián, Sarraute, Carlos, Vanthienen, Jan, Baesens, Bart

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Development and application of consumer credit scoring models using profit-based classification measures von Verbraken, Thomas, Bravo, Cristián, Weber, Richard, Baesens, Bart

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An empirical evaluation of the comprehensibility of decision table, tree and rule based predictive models von Huysmans, Johan, Dejaeger, Karel, Mues, Christophe, Vanthienen, Jan, Baesens, Bart

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Toward Comprehensible Software Fault Prediction Models Using Bayesian Network Classifiers von Dejaeger, K., Verbraken, T., Baesens, B.

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Time to default in credit scoring using survival analysis: a benchmark study von Dirick, Lore, Claeskens, Gerda, Baesens, Bart

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Active Trace Clustering for Improved Process Discovery von De Weerdt, Jochen, vanden Broucke, Seppe, Vanthienen, Jan, Baesens, Bart

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A Novel Profit Maximizing Metric for Measuring Classification Performance of Customer Churn Prediction Models von Verbraken, T., Verbeke, W., Baesens, B.

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Data Mining Techniques for Software Effort Estimation: A Comparative Study von Dejaeger, K., Verbeke, W., Martens, D., Baesens, B.

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Macro-Economic Factors in Credit Risk Calculations: Including Time-Varying Covariates in Mixture Cure Models von Dirick, Lore, Bellotti, Tony, Claeskens, Gerda, Baesens, Bart

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robROSE: A robust approach for dealing with imbalanced data in fraud detection von Baesens, Bart, Höppner, Sebastiaan, Ortner, Irene, Verdonck, Tim

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Explainable Deep Learning to Classify Royal Navy Ships von Baesens, Bart, Adams, Amy, Pacheco-Ruiz, Rodrigo, Baesens, Ann-Sophie, Broucke, Seppe Vanden

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Profit-based feature selection using support vector machines – General framework and an application for customer retention von Maldonado, Sebastián, Flores, Álvaro, Verbraken, Thomas, Baesens, Bart, Weber, Richard

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Process Mining for the multi-faceted analysis of business processes—A case study in a financial services organization von De Weerdt, Jochen, Schupp, Annelies, Vanderloock, An, Baesens, Bart

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Predicting take-up of home loan offers using tree- based ensemble models : a South African case study von Verster, Tanja, Harcharan, Samistha, Bezuidenhout, Lizette, Baesens, Bart

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How to improve prediction using behavior modification? von Baesens, Bart

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Practical Web Scraping for Data Science - Best Practices and Examples with Python von vanden Broucke, Seppe, Baesens, Bart

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Benchmarking Least Squares Support Vector Machine Classifiers von van Gestel, Tony, Suykens, Johan A.K., Baesens, Bart, Viaene, Stijn, Vanthienen, Jan, Dedene, Guido, de Moor, Bart, Vandewalle, Joos

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