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Cancellation Prediction for Flight Bookings using Machine Learning

Ahlam Ansari1 , Salim Mapkar2 , Ashad Shaikh3 , Maaz Khan4

Section:Research Paper, Product Type: Journal Paper
Volume-7 , Issue-3 , Page no. 319-321, Mar-2019

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v7i3.319321

Online published on Mar 31, 2019

Copyright © Ahlam Ansari, Salim Mapkar, Ashad Shaikh, Maaz Khan . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: Ahlam Ansari, Salim Mapkar, Ashad Shaikh, Maaz Khan, “Cancellation Prediction for Flight Bookings using Machine Learning,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.3, pp.319-321, 2019.

MLA Style Citation: Ahlam Ansari, Salim Mapkar, Ashad Shaikh, Maaz Khan "Cancellation Prediction for Flight Bookings using Machine Learning." International Journal of Computer Sciences and Engineering 7.3 (2019): 319-321.

APA Style Citation: Ahlam Ansari, Salim Mapkar, Ashad Shaikh, Maaz Khan, (2019). Cancellation Prediction for Flight Bookings using Machine Learning. International Journal of Computer Sciences and Engineering, 7(3), 319-321.

BibTex Style Citation:
@article{Ansari_2019,
author = {Ahlam Ansari, Salim Mapkar, Ashad Shaikh, Maaz Khan},
title = {Cancellation Prediction for Flight Bookings using Machine Learning},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {3 2019},
volume = {7},
Issue = {3},
month = {3},
year = {2019},
issn = {2347-2693},
pages = {319-321},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=3837},
doi = {https://doi.org/10.26438/ijcse/v7i3.319321}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i3.319321}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=3837
TI - Cancellation Prediction for Flight Bookings using Machine Learning
T2 - International Journal of Computer Sciences and Engineering
AU - Ahlam Ansari, Salim Mapkar, Ashad Shaikh, Maaz Khan
PY - 2019
DA - 2019/03/31
PB - IJCSE, Indore, INDIA
SP - 319-321
IS - 3
VL - 7
SN - 2347-2693
ER -

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Abstract

To generate revenue for any service-based industry, selling the right product to the right customer at a right time is the key aspect. Airline industry is an example of such an industry which could get benefit from knowing the right type of customers. This type of customers can be found out by analyzing behavioral patterns over a brief period of time. . Cancellation of flight ticket bookings is an interesting aspect from the perspective of Airline industries. If there is a system available which can predict about customer’s cancellation of booking then it can be exploited for huge profits and identifying customers which might possibly cancel their bookings is one of the many tasks that can be achieved by leveraging Data Analytics and Machine Learning techniques. Our goal is to design and implement a Classification model which will predict cancellation of ticket booked. We intend to achieve this goal by analyzing ticket booking data of a domestic Indian airline with the help of data analysis techniques to find some interesting patterns in the data. The predicted output will help to scale down the loss of Airline industries.

Key-Words / Index Term

Cancellation prediction, Flight data analytics, Machine learning

References

[1] W. McKinney, pandas: a python data analysis library, http://pandas.sourceforge.net [scipy2010].
[2] Fabian Pedregosa, Gaël Varoquaux, Alexandre Gramfort, Vincent Michel, Bertrand Thirion, Olivier Grisel, Mathieu Blondel, Peter Prettenhofer, Ron Weiss, Vincent Dubourg, Jake Vanderplas, Alexandre Passos, David Cournapeau, Matthieu Brucher, Matthieu Perrot and Edouard Duchesna: Scikit-learn: Machine Learning in Python, Journal of Machine Learning Research 12 (2011).
[3] O. Petraru: Airline passenger cancellations: modeling, forecasting and impacts on revenue management, Massachusetts Institute of Technology, 2016.
[4] 2. N. Antnio, A. Almeida, L. Nunes: Predicting hotel booking cancellations to decrease uncertainty and increase revenue, Tourism & Management Studies, 2017.
[5] 3. J. Howbert: Introduction to Machine Learning, University of Washington Bothell,2012.
[6] Matei Zaharia, Mosharaf Chowdhury, Tathagata Das, Ankur Dave, Justin Ma, Murphy McCauley, Michael J. Franklin, Scott Shenker, and Ion Stoica. Resilient Distributed Datasets: A Fault-Tolerant Abstraction for In-Memory Cluster Computing. In USENIX Symposium on Networked Systems Design and Implementation, 2012.
[7] X. Meng, J. Bradley, B. Yavuz, E. Sparks, S. Venkataraman, D. Liu, J. Freeman, D. Tsai, M. Amde, S. Owen, D. Xin, R. Xin, M. J. Franklin, R. Zadeh, M. Zaharia, and A. Talwalkar. MLlib: Machine learning in apache spark. Journal of Machine Learning Research, 17(34):1–7, 2016.
[8] Tianqi Chen and Carlos Guestrin. Xgboost: A scalable tree boosting system. In Proceedings of the 22Nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 785–794. ACM, 2016