Investigating customer churn in banking: A machine learning approach and visualization app for data science and management

Author:

Singh Pahul Preet,Anik Fahim Islam,Senapati Rahul,Sinha Arnav,Sakib NazmusORCID,Hossain Eklas

Publisher

Elsevier BV

Subject

Management Science and Operations Research,Information Systems and Management,Information Systems,Computer Science Applications,Artificial Intelligence,Management Information Systems

Reference37 articles.

1. Customer switching behavior analysis in the telecommunication industry via push-pull-mooring framework: a machine learning approach;Al-Mashraie;Comput. Ind. Eng.,2020

2. Anomaly-based intrusion detection in industrial data with SVM and random forests;Anton,2019

3. Performance evaluation of various classification techniques for customer churn prediction in E-commerce;Baghla;Microprocess. Microsyst.,2022

4. A comprehensive survey on support vector machine classification: applications, challenges and trends;Cervantes;Neurocomputing,2020

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3. Customer Churn Prediction: Leveraging Data Analysis and Machine Learning Approaches;2024 10th International Conference on Artificial Intelligence and Robotics (QICAR);2024-02-29

4. Customer Churn Prediction in Telecommunication and Banking using Machine Learning: A Systematic Literature Review;2024 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS);2024-01-28

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