Recommendations for U.s. Airlines Based on Customer Feedback

Us Airline

The U.S. Airline Passenger Satisfaction Dataset describes customer related satisfactory experience levels for all U.S. based airlines in 2015. The dataset details information for each customer as it relates to age, gender, type of travel, distance traveled, class type., and ultimately customer airline satisfaction level. Our team is set out to use a supervised classification methods in Machine Learning such as a Decision Tree, and Logistic Regression in order to predict customer satisfaction. The customer satisfaction is given by a score of satisfied (1) and dissatisfied/neutral (0). Our team will use 50% of the dataset as training data and the other 50% of the dataset as testing data. We expect the model to return an accuracy rating. Lastly, our team will use the satisfaction levels in order to find association between each rating system.