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[HTML][HTML] Hyperparameter optimization and combined data sampling techniques in machine learning for customer churn prediction: a comparative analysis
This paper explores the application of various machine learning techniques for predicting
customer churn in the telecommunications sector. We utilized a publicly accessible dataset …
customer churn in the telecommunications sector. We utilized a publicly accessible dataset …
A survey on machine learning methods for churn prediction
L Geiler, S Affeldt, M Nadif - International Journal of Data Science and …, 2022 - Springer
The diversity and specificities of today's businesses have leveraged a wide range of
prediction techniques. In particular, churn prediction is a major economic concern for many …
prediction techniques. In particular, churn prediction is a major economic concern for many …
Propension to customer churn in a financial institution: a machine learning approach
This paper examines churn prediction of customers in the banking sector using a unique
customer-level dataset from a large Brazilian bank. Our main contribution is in exploring this …
customer-level dataset from a large Brazilian bank. Our main contribution is in exploring this …
Predicting customer churn: A systematic literature review
Churn prediction is an active topic for research and machine learning approaches have
made significant contributions in this domain. Models built to address customer churn, aim to …
made significant contributions in this domain. Models built to address customer churn, aim to …
Effective ML techniques to predict customer churn
Customer churn is one of the most challenging problems that affects revenue and growth
strategy of a company. According to a recent Gartner Tech Marketing survey, 91% of C-level …
strategy of a company. According to a recent Gartner Tech Marketing survey, 91% of C-level …
An ensemble based approach using a combination of clustering and classification algorithms to enhance customer churn prediction in telecom industry
Mobile communication has become a dominant medium of communication over the past two
decades. New technologies and competitors are emerging rapidly and churn prediction has …
decades. New technologies and competitors are emerging rapidly and churn prediction has …
An effective strategy for churn prediction and customer profiling
L Geiler, S Affeldt, M Nadif - Data & Knowledge Engineering, 2022 - Elsevier
Customer churn prediction and profiling are two major economic concerns for many
companies. Different learning approaches have been proposed, however the a priori choice …
companies. Different learning approaches have been proposed, however the a priori choice …
Model optimization analysis of customer churn prediction using machine learning algorithms with focus on feature reductions
Currently, Customers are struggling to retain their business in today's competitive markets.
Thus, the issue of customer churn becomes a significant challenge for the industries. In …
Thus, the issue of customer churn becomes a significant challenge for the industries. In …
An empirical evaluation of stacked ensembles with different meta-learners in imbalanced classification
The selection of a meta-learner determines the success of a stacked ensemble as the meta-
learner is responsible for the final predictions of the stacked ensemble. Unfortunately, in …
learner is responsible for the final predictions of the stacked ensemble. Unfortunately, in …
What do we know about customer churn behaviour in the telecommunication industry? A bibliometric analysis of research trends, 1985–2019
The literature on telecommunications customer churn behaviour has grown in importance
and volume since the early 2000s. This study performed a quantitative bibliometric …
and volume since the early 2000s. This study performed a quantitative bibliometric …