Abstract
This research is going to be a machine learning project that aims to study the various factors that may play a role in forming customer satisfaction response and tries to figure out which attributes or combination of them are the driver of positive customer satisfaction. The research is going to use initially some dataset from Kaggle (explained in the section of data source) in order to run machine learning algorithms and creating a predictor that would help airlines in predicting which customers are satisfied and trying to have a proactive reaction in case of negative feedback, so we can make it up to the annoyed customer and get him satisfied. The research is going to examine several classification algorithms and tries to tune them in order to get the best result. Then will do experiments on resulting models and tries to find the optimal one among the others.
Publication Date
12-2022
Document Type
Master's Project
Student Type
Graduate
Degree Name
Professional Studies (MS)
Department, Program, or Center
Graduate Programs & Research (Dubai)
Advisor
Sanjay Modak
Advisor/Committee Member
Ehsan Warriach
Recommended Citation
AlHabbal, Mhd Ridwan, "Predicting & Optimizing Airlines Customer Satisfaction Using Classification" (2022). Thesis. Rochester Institute of Technology. Accessed from
https://repository.rit.edu/theses/11383
Campus
RIT Dubai
