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1 Ergebnisse
1
Data-Driven Retention Strategies: Exploring the Efficacy of..:
, In:
2024 International Conference on Distributed Computing and Optimization Techniques (ICDCOT)
,
Habelalmateen, Mohammed I
;
Dhandayuthapani V, Bala
;
Malathy, V
.. - p. 1-5 , 2024
Link:
https://doi.org/10.1109/ICDCOT61034.2024.10516017
RT T1 <cTitle>2024 International Conference on Distributed Computing and Optimization Techniques (ICDCOT)</cTitle>: T1 <Title>Data-Driven Retention Strategies: Exploring the Efficacy of Composite Deep Learning for Customer Churn Prediction in Telecommunications</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-10516017&Exemplar=1&LAN=DE A1 Habelalmateen, Mohammed I A1 Dhandayuthapani V, Bala A1 Malathy, V A1 Pramodhini, R A1 Ramakrishna, D YR 2024 K1 Industries K1 Measurement K1 Computational modeling K1 Predictive models K1 Feature extraction K1 Prediction algorithms K1 Communications technology K1 customer churn K1 features K1 gradient boosting K1 retention K1 telecom industry SP 1 OP 5 LK http://dx.doi.org/https://doi.org/10.1109/ICDCOT61034.2024.10516017 DO https://doi.org/10.1109/ICDCOT61034.2024.10516017 SF ELIB - SuUB Bremen
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