Predict the Prices of Airfares In India

Lal, Vishan (2022) Predict the Prices of Airfares In India. Masters thesis, Dublin, National College of Ireland.

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Abstract

The number of passengers traveling out using flight in India are increasing, and so are price changes. Seasonal and special event fluctuations are always seen in Indian airfares in multiple periods of the year. The proposed study will explore several data points related to forecasting airfares for different flights in India and use automated methods based on various machine learning models to predict airfares based on multiple characteristics. This research provides various exploratory analysis and insights to the customers which help them purchase their tickets at an optimal cost by exploring various factors, this research also showcases basic and advanced regression models that have been used to accurately predict the price of the airline for the customer. The basic and advanced regression models used in this research are Linear Regression, Decision tree as a regressor, Random Forest as a regressor, XG Boost regressor, K-neighbors regressor, Bagging Regressor, Extra trees regressor, Ridge regression and Lasso regression. Further, the models have been evaluated based on the Mean Average Error (MAE), Root Mean Square Error (RMSE), and adjusted R-Square values.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Muntean, Cristina Hava UNSPECIFIED
Subjects:	Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science H Social Sciences > HD Industries. Land use. Labor > Specific Industries > Aviation Industry Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Machine learning
Divisions:	School of Computing > Master of Science in Data Analytics
Depositing User:	Tamara Malone
Date Deposited:	19 May 2023 15:36
Last Modified:	19 May 2023 15:36
URI:	https://norma.ncirl.ie/id/eprint/6607

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