An efficient churn prediction model using gradient boosting machine and metaheuristic optimization

I AlShourbaji, N Helian, Y Sun, AG Hussien… - Scientific Reports, 2023 - nature.com
Customer churn remains a critical challenge in telecommunications, necessitating effective
churn prediction (CP) methodologies. This paper introduces the Enhanced Gradient …

ChurnNet: Deep Learning Enhanced Customer Churn Prediction in Telecommunication Industry

S Saha, C Saha, MM Haque, MGR Alam… - IEEE Access, 2024 - ieeexplore.ieee.org
In the Telecommunication Industry (TCI) customer churn is a significant issue because the
revenue of the service provider is highly dependent on the retention of existing customers. In …

Intelligent decision forest models for customer churn prediction

FE Usman-Hamza, AO Balogun, LF Capretz… - Applied Sciences, 2022 - mdpi.com
Customer churn is a critical issue impacting enterprises and organizations, particularly in the
emerging and highly competitive telecommunications industry. It is important to researchers …

Customer churn prediction model in cloud environment using DFE-WUNB: ANN deep feature extraction with weight updated tuned Naïve bayes classification with …

SA Panimalar, A Krishnakumar - Engineering Applications of Artificial …, 2023 - Elsevier
With progressing competitive market, different organizations were desperate to hold this
churn rate as minimum value, hence to achieve this, building an effective (CCP) customer …

[HTML][HTML] Empirical analysis of tree-based classification models for customer churn prediction

FE Usman-Hamza, AO Balogun, SK Nasiru, LF Capretz… - Scientific African, 2024 - Elsevier
Customer churn is a vital and reoccurring problem facing most business industries,
particularly the telecommunications industry. Considering the fierce competition among …

Factors, Predictability and Explainability of Mobile Telephony Customer Departure in Telecommunications Companies: A Systematic Review of the Literature

D Freire, D Mauricio, JLC Sequera, D Fiallo - IEEE Access, 2024 - ieeexplore.ieee.org
The telecommunications sector has experienced exponential growth since the year 2000,
reaching 5.31 trillion users by 2022, generating 1.07 trillion in revenue for …

Ensemble classification using balanced data to predict customer churn: a case study on the telecom industry

O Soleiman-garmabaki, MH Rezvani - Multimedia Tools and Applications, 2024 - Springer
Today, in addition to reactive methods, companies try to use proactive techniques for the
early detection of customer churn. Generally, gaining a new customer is more costly than …

A Multimodel‐Based Deep Learning Framework for Short Text Multiclass Classification with the Imbalanced and Extremely Small Data Set

J Tong, Z Wang, X Rui - Computational intelligence and …, 2022 - Wiley Online Library
Text classification plays an important role in many practical applications. In the real world,
there are extremely small datasets. Most existing methods adopt pretrained neural network …

Analysis implementation of the ensemble algorithm in predicting customer churn in telco data: A comparative study

RP Sari, F Febriyanto, AC Adi - Informatica, 2023 - informatica.si
Globalization and technological advancements in the telecommunication industry have led
to a significant rise in the number of operators, leading to intense market competition. This …

[PDF][PDF] Regression-Based Machine Learning Framework for Customer Churn Prediction in Telecommunication Industry

SI Ele, UR Alo, HF Nweke, OA Ofem - Journal of Advances in Information …, 2023 - jait.us
Customers' movement from one telecom provider to the other has become a foremost issue
in the telecommunication industry. This exacting issue has engendered stiff competition …