Explainable Stacking Machine Learning Ensemble for Predicting Airline Customer Satisfaction-Reference-Cited by-同舟云学术

Explainable Stacking Machine Learning Ensemble for Predicting Airline Customer Satisfaction

Published:2023 Issue: Volume: Page:41-56
ISSN:2367-3370
Container-title:Third Congress on Intelligent Systems
language:
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Author:

Pranav R.,Gururaja H. S.

Publisher

Springer Nature Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-19-9225-4_4

Reference26 articles.

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2. Tegar K, Lestari A, Pratiwi SW (2017) An analysis of airlines customer satisfaction by improving customer service performance. In: Global research on sustainable transport (GROST 2017). Atlantis Press, pp 619–628

3. García V (2019) Predicting airline customer satisfaction using k-nn ensemble regression models. Instituto de Ingeniería y Tecnología

4. Monmousseau P, Marzuoli A, Feron E, Delahaye D (2020) Impact of Covid-19 on passengers and airlines from passenger measurements: managing customer satisfaction while putting the US Air transportation system to sleep. Transp Res Interdisc Perspect 7:100179

5. Daudt F, Cinalli D, Garcia ACB (2021) Research on explainable artificial intelligence techniques: an user perspective. In: 2021 IEEE 24th international conference on computer supported cooperative work in design (CSCWD). IEEE, pp 144–149

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