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  1. Various machine learning models have been implemented to accurately find the flight ticket prices. With the help of feature selection techniques, our proposed model is able to predict the airfare price with an adjusted R squared score of 0.936.

  2. Comparing various Machine Learning models to predict flight ticket prices by considering a number of factors that can potentially affect the daily variation in their prices. - Flight-Ticket-Price-P...

  3. 3 maj 2024 · The "Flight Fare Prediction" project aims to develop an advanced predictive model leveraging machine learning algorithms to estimate and forecast airfare prices accurately.

  4. 1 lip 2019 · This paper deals with the problem of airfare prices prediction. For this purpose a set of features characterizing a typical flight is decided, supposing that these features affect the price...

  5. This project showcases a machine learning model developed to predict flight prices based on various features such as airline, source and destination cities, departure and arrival times, travel class, duration, and more.

  6. The Flight ticket prices increase or decrease every now and then depending on various factors like timing of the flights, destination, duration of flights. In the proposed system a predictive model will be created by applying machine learning algorithms to the collected historical data of flights.

  7. In this paper, we use a Machine Learning Regression approach to predict flight fare by providing basic details of departure date and time, arrival time, source, destination, number of stops and name of the airline. The results show that Random Forest Regression Model provides highly optimal results. Download Free PDF.

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