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Knowledge Discovery Using Least Squares Support Vector Machine Classifiers: A Direct Marketing Case.

S. Viaene, B. Baesens, T. Gestel, J. Suykens, D. den Poel, J. Vanthienen, B. Moor, and G. Dedene. PKDD, volume 1910 of Lecture Notes in Computer Science, page 657-664. Springer, (2000)

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Stijn Cleemput

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CORDIET - Healthcare: Extracting knowledge from electronic patient record data.J. Poelmans, H. der Mussele, G. Verheyden, S. Viaene, G. Dedene, S. Kuznetsov, and A. Neznanov. Nursing Informatics, volume 201 of Studies in Health Technology and Informatics, IOS Press, (2012)Benchmarking state-of-the-art classification algorithms for credit scoring.B. Baesens, T. Gestel, S. Viaene, M. Stepanova, J. Suykens, and J. Vanthienen. JORS, 54 (6): 627-635 (2003)How to move towards digital era governance: the case of VDAB.L. Danneels, and S. Viaene. DG.O, page 29-36. ACM, (2015)Identifying Digital Transformation Paradoxes.L. Danneels, and S. Viaene. Bus. Inf. Syst. Eng., 64 (4): 483-500 (2022)Text Mining Scientific Papers: A Survey on FCA-Based Information Retrieval Research.J. Poelmans, D. Ignatov, S. Viaene, G. Dedene, and S. Kuznetsov. ICDM, volume 7377 of Lecture Notes in Computer Science, page 273-287. Springer, (2012)A Case Study of Applying Boosting Naive Bayes to Claim Fraud Diagnosis.S. Viaene, R. Derrig, and G. Dedene. IEEE Trans. Knowl. Data Eng., 16 (5): 612-620 (2004)How BPM Impacts Jobs: An Exploratory Field Study.W. Mertens, J. den Bergh, S. Viaene, and F. Schröder-Pander. HICSS, page 1-10. IEEE Computer Society, (2011)Cost-sensitive learning and decision making revisited.S. Viaene, and G. Dedene. Eur. J. Oper. Res., 166 (1): 212-220 (2005)Exploring Capability Mapping as a Tool for Digital Transformation: Insights from a Case Study.J. Riel, G. Poels, and S. Viaene. BPMDS/EMMSAD@CAiSE, volume 479 of Lecture Notes in Business Information Processing, page 243-255. Springer, (2023)Toward Digital ERP: A Literature Review.B. Brabander, A. Looy, and S. Viaene. RCIS, volume 446 of Lecture Notes in Business Information Processing, page 685-693. Springer, (2022)

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Knowledge Discovery Using Least Squares Support Vector Machine Classifiers: A Direct Marketing Case.

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Stijn Cleemput

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copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Knowledge Discovery Using Least Squares Support Vector Machine Classifiers: A Direct Marketing Case.

Please choose a person to relate this publication to

Stijn Cleemput

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Knowledge Discovery Using Least Squares Support Vector Machine Classifiers: A Direct Marketing Case.