Airline-Passenger-Satisfaction

The "Airline Passenger Satisfaction Prediction Project" through Machine Learning focuses on developing a predictive model that can accurately assess and forecast passenger satisfaction levels. By integrating machine learning algorithms with airline data, the project aims to provide airlines with valuable insights to make informed decisions and improve their services to meet and exceed customer expectations.

About Dataset

Context

This dataset contains an airline passenger satisfaction survey. What factors are highly correlated to a satisfied (or dissatisfied) passenger? Can you predict passenger satisfaction?

Content

• Gender: Gender of the passengers (Female, Male)

• Customer Type: The customer type (Loyal customer, disloyal customer)

• Age: The actual age of the passengers

• Type of Travel: Purpose of the flight of the passengers (Personal Travel, Business Travel)

• Class: Travel class in the plane of the passengers (Business, Eco, Eco Plus)

• Flight distance: The flight distance of this journey

• Inflight wifi service: Satisfaction level of the inflight wifi service (0:Not Applicable;1-5)

• Departure/Arrival time convenient: Satisfaction level of Departure/Arrival time convenient

• Ease of Online booking: Satisfaction level of online booking

• Gate location: Satisfaction level of Gate location

• Food and drink: Satisfaction level of Food and drink

• Online boarding: Satisfaction level of online boarding

• Seat comfort: Satisfaction level of Seat comfort

• Inflight entertainment: Satisfaction level of inflight entertainment

• On-board service: Satisfaction level of On-board service

• Leg room service: Satisfaction level of Leg room service

• Baggage handling: Satisfaction level of baggage handling

• Check-in service: Satisfaction level of Check-in service

• Inflight service: Satisfaction level of inflight service

• Cleanliness: Satisfaction level of Cleanliness

• Departure Delay in Minutes: Minutes delayed when departure

• Arrival Delay in Minutes: Minutes delayed when Arrival

• Satisfaction: Airline satisfaction level(Satisfaction, neutral or dissatisfaction)

This data set contains a survey on air passenger satisfaction. The following classification problem is set:

It is necessary to predict which of the two levels of satisfaction with the airline the passenger belongs to:

1. Satisfaction
2. Neutral or dissatisfied

Flask Prediction UI

Flask Result UI