The data we have at hand is of passengers and their feedback regarding their flight experience. Each row is one passenger. Apart from the feedback from the customers accross various attributes(15 in total) like food, online_support, cleanliness etc, we have data about the customers' age, loyalty to the airline, gender and class. The target column is a binary variable which tells us if the customer is satisfied or neutral/dissatisfied The task at hand is to analyze reasons for customers' satisfaction or dissatisfaction. And finally, we build a model to predict customer satisfaction using all or some of the data we have. The deatiled analysis can be found in the Rmd file.
shoaib555/Customer-flight-satisfaction-prediction
The data at hand is of flight satisfaction survey along with the customer flight information, the task at hand is to build a model that predicts satisfaction/dissatisfaction given the various attributes
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