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Cross-company customer churn prediction in telecommunication: A comparison of data transformation methods., , , , , , and . Int J. Information Management, (2019)A Comparison of Two Oversampling Techniques (SMOTE vs MTDF) for Handling Class Imbalance Problem: A Case Study of Customer Churn Prediction., , , , and . WorldCIST (1), volume 353 of Advances in Intelligent Systems and Computing, page 215-225. Springer, (2015)Fixed point optimization of deep convolutional neural networks for object recognition., , and . ICASSP, page 1131-1135. IEEE, (2015)Compromised user credentials detection in a digital enterprise using behavioral analytics., , , , , , and . Future Generation Comp. Syst., (2019)Special Issue on Knowledge Discovery in Big Data (KDBD)., and . J. Grid Comput., 17 (2): 205-208 (2019)A Prudent Based Approach for Customer Churn Prediction., , , and . BDAS, volume 521 of Communications in Computer and Information Science, page 320-332. Springer, (2015)Customer Churn Prediction in Telecommunication Industry: With and without Counter-Example., , , and . MICAI (2), volume 8857 of Lecture Notes in Computer Science, page 206-218. Springer, (2014)Learning separable fixed-point kernels for deep convolutional neural networks., , and . ICASSP, page 1065-1069. IEEE, (2016)Semantic Based Ontology Driven Feature Interaction Detection & Modeling., , , , and . ICISA, page 1-5. IEEE, (2013)Site selection for food distribution using rough set approach and TOPSIS method., , , , and . Journal of Intelligent and Fuzzy Systems, 29 (6): 2413-2419 (2015)