JOURNAL ARTICLE

Customer Churn Prediction Using Machine Learning Algorithms

Pallavi HangargeGunjan JadhavVaishnavi JanagaveSujal KadamProf. P. S. Pise

Year: 2023 Journal:   International Journal for Research in Applied Science and Engineering Technology Vol: 11 (4)Pages: 2374-2376   Publisher: International Journal for Research in Applied Science and Engineering Technology (IJRASET)

Abstract

Abstract: Customer churn is a serious problem in the telecommunications industry and occurs more often. Customer churn is the percentage of customers that stopped using your company's product or service during a certain time frame. One of the most important problems in predicting customer churn is the imbalanced data, which has been tried to be solved and compared with different methods. The machine learning algorithms will be use in this paper are Decision Tree, Support Vector Machine, Random Forest . Also, the performance of support vector were better than other algorithms.

Keywords:
Computer science Random forest Decision tree Support vector machine Machine learning Customer retention Product (mathematics) Artificial intelligence Service (business) Frame (networking) Algorithm Tree (set theory) Data mining Service quality Marketing Business Telecommunications Mathematics

Metrics

1
Cited By
0.31
FWCI (Field Weighted Citation Impact)
6
Refs
0.57
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Customer churn and segmentation
Social Sciences →  Business, Management and Accounting →  Marketing
Customer Service Quality and Loyalty
Social Sciences →  Business, Management and Accounting →  Organizational Behavior and Human Resource Management
Big Data and Business Intelligence
Social Sciences →  Business, Management and Accounting →  Management Information Systems

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