Exploratory Data Analysis and Prediction of Passenger Satisfaction with Airline services

The airline industry has bloomed greatly after the COVID-19. The customer satisfaction about the airlines is a key factor in the success of the airline industry. This study focuses on several aspects affecting the services of the airline and a comparative study is made by applying various algorithms like Gaussian Naive Bayes, Gradient Boosting Classifier, Linear Support Vector Machine, Logistic Regression, Multilayer Perceptron Classifier and Random Forest Classifier. The result of our analysis to predict the customer satisfaction as satisfied or unsatisfied shows that the Gradient Boosting Algorithm achieved an accuracy of 96 % and it is identified that the key feature of the analysis is the boarding process and Wi-Fi services.