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
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