A comparative study of statistical and intelligent classification models for predicting airlines passenger management satisfaction

A comparative study of statistical and intelligent classification models for predicting airlines passenger management satisfaction

This paper compares Statistical and Intelligent classification models in predicting passenger satisfaction with airlines. It seeks to identify the most accurate and reliable model amongst GLM, Robust Regression, MARS, KNN and Neural Networks. Methodology. These models were analyzed using a set of pe...

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Bibliographic Details
Main Authors: Mohammed Alharithi, Ehab M. Almetwally, Omar Alotaibi, Marwa M. Eid, El-Sayed M. El-kenawy, Alaa A. Elnazer
Format: Article
Language:English
Published: Elsevier 2025-04-01
Series:Alexandria Engineering Journal
Subjects:
Airline passenger satisfaction
Predictive modeling
Logistic regression
K-Nearest Neighbor (KNN)
Neural networks
Machine learning regression
Online Access:http://www.sciencedirect.com/science/article/pii/S1110016825001358
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