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Applying the CG-logistic Regression Method to Predict the Customer Churn Problem
Research article (2018 5th International Conference on Industrial Economics System and Industrial Security Engineering (IEIS), 2018) · cited 11× · AI/ML
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APA4ort.xyz Knowledge Graph. (2026). Applying the CG-logistic Regression Method to Predict the Customer Churn Problem. Retrieved May 24, 2026, from https://4ort.xyz/entity/applying-the-cg-logistic-regression-method-to-predict-the-customer-churn-problem
MLA“Applying the CG-logistic Regression Method to Predict the Customer Churn Problem.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/applying-the-cg-logistic-regression-method-to-predict-the-customer-churn-problem.
BibTeX@misc{4ortxyz_applying-the-cg-logistic-regression-method-to-predict-the-customer-churn-problem_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Applying the CG-logistic Regression Method to Predict the Customer Churn Problem}}, year = {2026}, url = {https://4ort.xyz/entity/applying-the-cg-logistic-regression-method-to-predict-the-customer-churn-problem}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Applying the CG-logistic Regression Method to Predict the Customer Churn Problem — https://4ort.xyz/entity/applying-the-cg-logistic-regression-method-to-predict-the-customer-churn-problem (retrieved 2026-05-24)
