A Comparison Between Machine Learning Models for Airticket Price Prediction

Airline ticket prices fluctuate, even for the same flight. Airlines are focusing on implementing various algorithms to adjust prices to maximize revenue from system-generated fares, allowing them to fill the maximum number of seats available. Because of the fierce competition among airline services, these models are unavailable to the general public. Recent advances in Machine Learning (ML) make it possible to model price fluctuation. This study presents a new application based on two Kaggle datasets. To forecast the price of airline tickets, it employs well-known machine learning algorithms like Random Forest and Randomized Search CV. This predictive model will assist passengers in purchasing decisions by predicting how air ticket prices will fluctuate.