Hotel Booking Prediction using Machine Learning

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Abstract: In this Project ‘Hotel Booking Prediction’, an accurate booking cancellation forecast by which user know the things related to hotel bookings very earlier. Booking cancellation has a significant effect on revenue which essentially affects request the board choices in the inn business. To reduce the cancellation effect, the hotel applies the cancellation model as the key to addressing this problem with the machine learning-based system developed. By combining data science tools and capabilities with human judgement and interpretation, this project aims to demonstrate how the predictive analysis of the model can contribute to synthesizing and predict about booking cancellation forecasting. Furthermore, this project aims, by detailing the full prediction & analysis, to give relaxation to user who want to apply in particular hotel. By Implement Various Algorithms like Logistic, KNN, Random Forest, Decision Tree, etc. to classify the data and also use Evaluation Matrix to separate categorical data in particular type, user can know the prediction up to the desired level. It prevents the hotel as well as Tourists to poor dealing of room. User/Customer have to enter certain field by which this model detects his prediction about the cancellation. Keywords: Logistic Regression, KNN, Random forest, Decision Tree, Evaluation Matrix.