Airline Choice: A Comparison of Classifiers in Traditional Analysis vs Decision Trees

Airline Choice: A Comparison of Classifiers in Traditional Analysis vs Decision Trees

Archana Shrivastava, P. James Daniel Paul, J.K. Sharma
Copyright: © 2020 |Pages: 20
DOI: 10.4018/IJBAN.2020040103
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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.
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Methodology

This paper uses the data from the popular multiband ticket-booking site called www.makemytrip.com. The search for the price of tickets between London and New Delhi were 30 days before the travel date and 15 days before the travel date. 98 different price combinations were obtained and then the data was analyzed. But before the analysis of the data the literature on similar studies were collected and analyzed. The route Delhi to London was chosen arbitrarily. We have used Word Cloud, SPSS, Tableau, and WEKA for analysis and visualization.

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