References
- AllisonPDLogistic Regression Using the SAS System: Theory and Application2001
- AlonsoFCaraça-ValenteJPGonzálezALMontesCCombining expert knowledge and data mining in a medical diagnosis domainExpert Syst Appl200223436737510.1016/S0957-4174(02)00072-6
- AltendorfERestificarEDietterichTLearning from sparse data by exploiting monotonicity constraintsProceedings of the 21st Conference on Uncertainty in Artificial Intelligence20051825
- AnandSSBellDAHughesJGThe role of domain knowledge in data miningProceedings of the Fourth International Conference on Information and Knowledge Management19953743
- BaesensBSetionoRMuesCVanthienenJUsing neural network rule extraction and decision tables for credit-risk evaluationMngt Sci200349331232910.1287/mnsc.49.3.312.12739
- BaesensBVan GestelTViaeneSStepanovaMSuykensJVanthienenJBenchmarking state-of-the-art classification algorithms for credit scoringJ Opl Res Soc200354662763510.1057/palgrave.jors.2601545
- Ben-DavidAMonotonicity maintenance in information-theoretic machine learning algorithmsMach Learn19951912943
- BuckinxWVan den PoelDCustomer base analysis: Partial defection of behaviorally-loyal clients in a noncontractual FMCG retail settingEur J Opl Res2005164125226810.1016/j.ejor.2003.12.010
- BurezJVan den PoelDCRM at a pay-TV company: Using analytical models to reduce customer attrition by targeted marketing for subscription servicesExpert Syst Appl200732227728810.1016/j.eswa.2005.11.037
- CoussementKVan den PoelDChurn prediction in subscription services: An application of support vector machines while comparing two parameter-selection techniquesExpert Syst Appl200834131332710.1016/j.eswa.2006.09.038
- DeLongERDeLongDMClarke-PearsonDLComparing the areas under two or more correlated receiver operating characteristic curves: A nonparametric approachBiometrics198844383784510.2307/2531595
- FaderPSHardieBGSLeeKLRFM and CLV: Using iso-value curves for customer base analysisJ Market Res200542441543010.1509/jmkr.2005.42.4.415
- FeeldersAPardoelMPruning for monotone classification treesAdvances In Intelligent Data Analysis2003112
- HwangHJungTSuhEAn LTV model and customer segmentation based on customer value: A case study on the wireless telecommunication industryExpert Syst Appl200426218118810.1016/S0957-4174(03)00133-7
- JainDSinghSSCustomer lifetime value research in marketing: A review and future directionsJ Interact Market2002162344610.1002/dir.10032
- KimSShinKSParkKAn application of support vector machines for customer churn analysis: Credit card caseICNC 2005, Lect Notes Comput Sci20053611636647
- KimSJungTSuhEHwangHCustomer segmentation and strategy development based on customer lifetime value: A case studyExpert Syst Appl200631110110710.1016/j.eswa.2005.09.004
- KopanasIAvourisNMDaskalakiSThe role of domain knowledge in a large scale data mining projectMethods and Applications of Artificial Intelligence, Proceedings for the Second Hellenic Conference on AI, SETN 20022002288299
- LarivièreBVan den PoelDInvestigating the role of product features in preventing customer churn, by using survival analysis and choice modeling: The case of financial servicesExpert Syst Appl200427227728510.1016/j.eswa.2004.02.002
- LaroseDTDiscovering Knowledge in Data: An Introduction to Data Mining2005
- MalthouseECBlattbergRCCan we predict customer lifetime value?J Interact Market200519121610.1002/dir.20027
- Martens D and Baesens B (2009). Building acceptable classification models. Ann Inf Syst forthcoming.
- MartensDDe BackerMHaesenRBaesensBMuesCVanthienenJAnt-Based approach to the knowledge fusion problemANTS Workshop 200620068495
- MasandBDattaPManiDRLiBCHAMP: A prototype for automated cellular churn predictionData Min Knowl Disc19993221922510.1023/A:1009873905876
- NathSVBeharaRSCustomer churn analysis in the wireless industry: A data mining approachProceedings of the 34th Annual Meeting of the Decision Sciences Institute2003505510
- NeslinSAGuptaSKamakuraWLuJMasonCDefection detection: measuring and understanding the predictive accuracy of customer churn modelsJ Market Res200643220421110.1509/jmkr.43.2.204
- QuinlanJRC4.5: Programs for Machine Learning1993
- SillJMonotonic networksAdvances in Neural Information Processing Systems1998661667
- Van GestelTMartensDBaesensBFeremansDHuysmansJVanthienenJForecasting and analyzing insurance companies' ratingsInt J Forecasting200723351352910.1016/j.ijforecast.2007.05.001
- VanthienenJDriesEIllustration of a decision table tool for specifying and implementing knowledge based systemsInt J Artif Int Tools19943226728810.1142/S0218213094000133
- VanthienenJWetsGFrom decision tables to expert system shellsData Knowl Eng199413326528210.1016/0169-023X(94)00020-4
- VanthienenJMuesCAertsAAn illustration of verification and validation in the modelling phase of KBS developmentData Knowl Eng199827333735210.1016/S0169-023X(98)80003-7
- VelikovaMDanielsHDecision trees for monotone price modelsComput Mngt Sci200413–4231244
- VelikovaMDanielsHFeeldersASolving partially monotone problems with neural networksTransactions on Engineering, Computing, and Technology20068287
- WetsGVanthienenJPiramuthuSExtending a tabular knowledge based framework with feature selectionExpert Syst Appl199713210911910.1016/S0957-4174(97)00012-2
- WittenIHFrankEData Mining: Practical Machine Learning Tools and Techniques2005
- Zhao Y, Li B, Li X, Liu W and Ren S (2005). Customer churn prediction using improved one-class support vector machine. ADMA 2005, Lecture Notes in Artificial Intelligence, Vol. 3584. pp. 300–306.