The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Airline Choice: A Comparison of Classifiers in Traditional Analysis vs Decision Trees
|
|
Author(s): Archana Shrivastava (Amity School of Business, Amity University Uttarpradesh, Noida, India), P. James Daniel Paul (Ernst and Young LLP, Bengaluru, India)and J.K. Sharma (Amity School of Business, Amity University Uttarpradesh, Noida, India)
Copyright: 2020
Volume: 7
Issue: 2
Pages: 20
Source title:
International Journal of Business Analytics (IJBAN)
Editor(s)-in-Chief: John Wang (Montclair State University, USA)
DOI: 10.4018/IJBAN.2020040103
Purchase
|
Abstract
Widespread use of e-commerce in the airline industry is generating data at unprecedented scale, thus rendering it amenable to decision analysis. Classification accuracy is one of the key factors in forecasting and in the decision sciences. The traditional classification analysis was carried out by several methods such as ANOVA, Logit, Probit. However, for decision analysis algorithms and decision trees have emerged for classification analysis. The objective of the article is to analyze the airline choice data using the traditional ANOVA and compare them with the decision trees and different algorithms.
Related Content
|
Di Kevin Gao, Andrew Haverly, Sudip Mittal, Jiming Wu, Jingdao Chen.
© 2024.
19 pages.
|
|
Vijayabanu C., Karthikeyan S., Gayathri R..
© 2023.
13 pages.
|
|
Ganeshkumar C., Jeganathan Gomathi Sankar, Arokiaraj David.
© 2023.
17 pages.
|
|
Gladys Marisol Merino Castro, Higinio Guillermo Wong Aitken, Alicia Alicia Calvanapon.
© 2023.
14 pages.
|
|
Simonetta Pattuglia, Sara Amoroso.
© 2023.
15 pages.
|
|
Leigh Wang.
© 2023.
4 pages.
|
|
Bhawna Agarwal, Merlin Mythili Nelson.
© 2023.
15 pages.
|
|
|