MeshalAlamr/flight-price-prediction
Predicting flight ticket prices using a random forest regression model based on scraped data from Kayak. A Kayak scraper is also provided.
The project trains on 55,363 flight records across multiple source-destination pairs, engineering features like total stops, airline-averaged pricing, and flight duration to achieve ~$61.87 MAE prediction accuracy. Beyond the core regression model, it includes a companion Android app that surfaces average estimated prices for selected routes and months, bridging the prediction pipeline to end-user flight search workflows.
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Jul 26, 2023
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