International Journal For Multidisciplinary Research

E-ISSN: 2582-2160     Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 6 Issue 5 September-October 2024 Submit your research before last 3 days of October to publish your research paper in the issue of September-October.

A Machine Learning Based Approach to Predict Customer Churn in Airline Industry : The Case of India

Author(s) Krushna Bembade, Soumitra Das, Aditya Dixit, Aryan Raut, Aniket Yadav
Country India
Abstract This research addresses the challenge of customer churn in the airline industry by leveraging machine learning (ML) techniques to predict and understand the factors influencing customer attrition. Drawing on a comprehensive dataset encompassing customer demographics, flight history, and service interactions, we employed rigorous data preprocessing techniques and evaluated various ML algorithms
Keywords Customer churn prediction, Machine Learning, Random Forest, Decision Trees, Support Vector Machine, Predictive Analytics, Customer Segmentation, Customer Lifetime Value, Classification Algorithms, Customer Feedback Loop, Customer Satisfaction Surveys
Field Engineering
Published In Volume 6, Issue 2, March-April 2024
Published On 2024-04-28
Cite This A Machine Learning Based Approach to Predict Customer Churn in Airline Industry : The Case of India - Krushna Bembade, Soumitra Das, Aditya Dixit, Aryan Raut, Aniket Yadav - IJFMR Volume 6, Issue 2, March-April 2024. DOI 10.36948/ijfmr.2024.v06i02.18026
DOI https://doi.org/10.36948/ijfmr.2024.v06i02.18026
Short DOI https://doi.org/gtsg7w

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