Predictive Analytics in Hotel Recommendations Using Machine Learning

In a world where travellers want the perfect stay, a new system emerges as the one that goes beyond simple hotel recommendations. By analysing details like interaction words and prices, it predicts hotel ratings using a powerful Random Forest Regressor which performs better than methods like Linear Regressor. With careful data processing and encoding, it achieves high accuracy, measured through precise metrics like RMSE, MSE and Max Error. It achieves a great RMSE score of 0.424. This system offers a scalable solution, turning every hotel suggestion into a personalized experience, redefining the way people find their ideal stay.