An ensemble based approach using a combination of clustering and classification algorithms to enhance customer churn prediction in telecom industry

SF Bilal, AA Almazroi, S Bashir, FH Khan… - PeerJ Computer …, 2022 - peerj.com
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 …

Research trends in customer churn prediction: a data mining approach

Z Tianyuan, S Moro - World conference on information systems and …, 2021 - Springer
This study aims to present a very recent literature review on customer churn prediction
based on 40 relevant articles published between 2010 and June 2020. For searching the …

Customer churn prediction in telecommunication industry using machine learning classifiers

NI Mohammad, SA Ismail, MN Kama… - Proceedings of the 3rd …, 2019 - dl.acm.org
Customer churn is one of the main problems in telecommunication industry. This study aims
to identify the factors that influence customer churn and develop an effective churn …

[PDF][PDF] Predicting student enrollments and attrition patterns in higher educational institutions using machine learning.

S Shilbayeh, A Abonamah - Int. Arab J. Inf. Technol., 2021 - researchgate.net
In higher educational institutions, student enrollment management and increasing student
retention are fundamental performance metrics to academic and financial sustainability. In …

[PDF][PDF] Review of Customer Churn Analysis Studies in Telecommunications Industry.

F Kayaalp - Karaelmas Science & Engineering Journal/Karaelmas …, 2017 - researchgate.net
Churn Analysis is one of the world wide used analysis on Subscription Oriented Industries to
analyze customer behaviors to predict the customers which are about to leave the service …

Customer churn modeling in telecommunication using a novel multi-objective evolutionary clustering-based ensemble learning

K Faraji Googerdchi, S Asadi, SM Jafari - Plos one, 2024 - journals.plos.org
Customer churn prediction is vital for organizations to mitigate costs and foster growth.
Ensemble learning models are commonly used for churn prediction. Diversity and prediction …

Development of a Predictive Model of Student Attrition Rate

G Sani, F Oladipo, E Ogbuju, FJ Agbo - Journal of Applied Artificial …, 2022 - sabapub.com
Enrollment in courses is a key performance indicator in educational systems for maintaining
academic and financial viability. Today, a lot of factors, comprising demographic and …

Customer Churn Analysis for Live Stream E-Commerce Platforms by Using Decision Tree Method

A Shi, CY Lim, SL Ang - International Conference on Advanced …, 2023 - Springer
The popularity of online live stream sales as a successful business model has increased
due to its effectiveness in promoting sales quickly. This growth has been further accelerated …

Predicting base station return on investment in the telecommunications industry: Machine‐learning approaches

C Şahin - Intelligent Systems in Accounting, Finance and …, 2023 - Wiley Online Library
Investment in the right location ensures sustainable competition. In the telecommunication
sector, the number of base stations (BSs) is one of the most significant investment …

Comparative study on different classification models for customer churn problem

A Kinge, Y Oswal, T Khangal, N Kulkarni… - Machine Intelligence and …, 2022 - Springer
Customer churn is a significant issue and one of the most pressing challenges for large
businesses. Companies are working to create methods to predict prospective client churn …