A Swish RNN based customer churn prediction for the telecom industry with a novel feature selection strategy
R Sudharsan, EN Ganesh - Connection Science, 2022 - Taylor & Francis
Owing to saturated markets, fierce competition, dynamic criteria, along with introduction of
new attractive offers, the considerable issue of customer churn was faced by the …
new attractive offers, the considerable issue of customer churn was faced by the …
B2C E-commerce customer churn prediction based on K-means and SVM
X Xiahou, Y Harada - Journal of Theoretical and Applied Electronic …, 2022 - mdpi.com
Customer churn prediction is very important for e-commerce enterprises to formulate
effective customer retention measures and implement successful marketing strategies …
effective customer retention measures and implement successful marketing strategies …
A review of evaluation metrics in machine learning algorithms
G Naidu, T Zuva, EM Sibanda - Computer Science On-line Conference, 2023 - Springer
With the increase in the adoption rate of machine learning algorithms in multiple sectors, the
need for accurate measurement and assessment is imperative, especially when classifiers …
need for accurate measurement and assessment is imperative, especially when classifiers …
Deep churn prediction method for telecommunication industry
Being able to predict the churn rate is the key to success for the telecommunication industry.
It is also important for the telecommunication industry to obtain a high profit. Thus, the …
It is also important for the telecommunication industry to obtain a high profit. Thus, the …
Machine Learning and Deep Learning technique used in Customer Churn Prediction:-A Review
A Raj, D Vetrithangam - 2023 International Conference on …, 2023 - ieeexplore.ieee.org
Churn Prediction is crucial in a number of service-based businesses, including the telecom
sector, life insurance, hospitality, banking, and gaming. A Prediction of consumer churn in …
sector, life insurance, hospitality, banking, and gaming. A Prediction of consumer churn in …
Artificial intelligence based customer churn prediction model for business markets
J Faritha Banu, S Neelakandan… - Computational …, 2022 - Wiley Online Library
The introduction of artificial intelligence (AI) and machine learning (ML) technologies in
recent years has resulted in improved company performance. Customer churn forecast is a …
recent years has resulted in improved company performance. Customer churn forecast is a …
[Retracted] A Prediction Model of Customer Churn considering Customer Value: An Empirical Research of Telecom Industry in China
M Zhao, Q Zeng, M Chang, Q Tong… - Discrete Dynamics in …, 2021 - Wiley Online Library
Customer churn will cause the value flowing from customers to enterprises to decrease. If
customer churn continues to occur, the enterprise will gradually lose its competitive …
customer churn continues to occur, the enterprise will gradually lose its competitive …
Impact of hyperparameters on deep learning model for customer churn prediction in telecommunication sector
A Dalli - Mathematical Problems in Engineering, 2022 - Wiley Online Library
In this paper, in order to predict a customer churn in the telecommunication sector, we have
analysed several published articles that had used machine learning (ML) techniques …
analysed several published articles that had used machine learning (ML) techniques …
Hybrid model for profit-driven churn prediction based on cost minimization and return maximization
P Jiang, Z Liu, L Zhang, J Wang - Expert Systems with Applications, 2023 - Elsevier
Customer churn prediction is widely used to detect potential churners, which stimulates
customer retention, and decrease churn loss. Most customer churn prediction models …
customer retention, and decrease churn loss. Most customer churn prediction models …
Swarm intelligence goal-oriented approach to data-driven innovation in customer churn management
One type of data-driven innovations in management is data-driven decision making.
Confronted with a big amount of data external and internal to their organization's managers …
Confronted with a big amount of data external and internal to their organization's managers …