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Telecom churn prediction and used techniques, datasets and performance measures: a review
Customer churn prediction in telecommunication industry is a very essential factor to be
achieved and it makes direct impact to customer retention and its revenues. Develo** a …
achieved and it makes direct impact to customer retention and its revenues. Develo** a …
Intelligent data analysis approaches to churn as a business problem: a survey
Globalization processes and market deregulation policies are rapidly changing the
competitive environments of many economic sectors. The appearance of new competitors …
competitive environments of many economic sectors. The appearance of new competitors …
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 …
Predicting employee attrition using machine learning techniques
There are several areas in which organisations can adopt technologies that will support
decision-making: artificial intelligence is one of the most innovative technologies that is …
decision-making: artificial intelligence is one of the most innovative technologies that is …
Profit-driven fusion framework based on bagging and boosting classifiers for potential purchaser prediction
Accurately identifying potential purchasers (PPers) is pivotal for enhancing an enterprise's
core competitiveness in a competitive market. Although existing research focused on …
core competitiveness in a competitive market. Although existing research focused on …
[PDF][PDF] Customer churn prediction in telecommunication industry using deep learning
Without proper analysis and forecasting, industries will find themselves repeatedly churning
customers, which the telecom industry in particular cannot afford. A predictable model for …
customers, which the telecom industry in particular cannot afford. A predictable model for …
A data mining-based framework for supply chain risk management
Increased risk exposure levels, technological developments and the growing information
overload in supply chain networks drive organizations to embrace data-driven approaches …
overload in supply chain networks drive organizations to embrace data-driven approaches …
Why customer satisfaction is important to business?
AA Hamzah, MF Shamsudin - Journal of Undergraduate Social Science …, 2020 - abrn.asia
This paper explores the importance of customer in strategic marketing in the values of
customer satisfaction and loyalty. The role of customer for organizations in the 21st century …
customer satisfaction and loyalty. The role of customer for organizations in the 21st century …
Machine-learning techniques for customer retention: A comparative study
SF Sabbeh - … Journal of advanced computer Science and …, 2018 - search.proquest.com
Nowadays, customers have become more interested in the quality of service (QoS) that
organizations can provide them. Services provided by different vendors are not highly …
organizations can provide them. Services provided by different vendors are not highly …
An empirical comparison of techniques for the class imbalance problem in churn prediction
Class imbalance brings significant challenges to customer churn prediction. Many solutions
have been developed to address this issue. In this paper, we comprehensively compare the …
have been developed to address this issue. In this paper, we comprehensively compare the …