A Machine Learning Chronicle in Airfares for Pricing the Clouds

Abstract

The subject of airfare is examined in this paper. As a result, a collection of factors that characterize a typical flight are selected under the presumption that they have an impact on airline ticket costs. The price of a plane ticket is influenced by the length of the trip, the location, the schedule, and several other factors, like holidays or vacations. Therefore, many people will surely save time and effort by having a basic awareness of airline expenses prior to making trip arrangements. The performance of the seven different machine learning (ML) models used to anticipate the price of airline tickets is compared after three datasets were analysed to acquire insight into airline fares. The objective is to investigate the factors that influence flight prices. The data can then be used to build a system that can predict how much a flight will cost.