A Machine Learning Based Approach to Predicting Flight Fares for Indian Airlines

Flight ticket prices fluctuate drastically depending upon a number of factors such as fuel prices, government regulations, routes taken, festival seasons, airline policies, etc. Flight aggregator websites fail to educate the consumers on an optimally effective timing for purchasing tickets without any data analyses backing them up. The proposed work helps to predict the flight ticket based on various factors using Machine Learning (ML) approaches. The proposed work analyses the Indian Domestic Airlines data on various machine learning models for computing expected future prices of Indian Airlines. The proposed model can be used by airlines to reduce human error in ticket pricing, manage price offerings to meet revenue targets, and increase profits. Experimental results helps to identify the best ML approach and results in higher statistical evaluation scores.