Tour Planner Application Using Machine Learning

Abstract

Tourism is a fast-growing industry and is the most demanding for psychological and physiological health. With the advancement of this sector, machine learning can improve both the financial and punctuality of tourists. Most tourists are curious about the destination and budget estimation. To help tourists with proper destination choice and budget calculation, we have proposed an application with machine learning. The application generates predictions based on real user data we have collected and uses algorithms to give the best experience. To generate the most accurate results, complex algorithms were implemented, such as Random Forest, Naive Bayes, Decision Tree, and K-Nearest Nebert (KNN).