Predictive Analytics Report: Predicting Lounge Ratings at Airports

This report presents a predictive analytics analysis of airport lounge ratings, based on a survey conducted by AQA and Skytrax. The study aims to predict overall lounge ratings using various factors like comfort, cleanliness, and staff service. The analysis employs logistic regression, k-NN, and decision tree models. The decision tree model demonstrated the best accuracy in predicting overall ratings. The report includes data preparation steps, relationship discovery, and detailed processes and outputs for each model, including accuracy, precision, and AUC values. The findings indicate positive customer recommendations for lounges, influenced significantly by factors such as overall rating, comfort, and staff service. The report recommends the use of the decision tree model for future evaluations of airport quality and suggests that Skytrax continue to collect and analyze data to improve lounge services and passenger experiences.