Trip budget prediction using multivariate linear regression algorithm in machine learning

Abstract

Trip budget prediction based on the number of people, distance and duration of a local travel agency using a multivariate linear regression algorithm. Real-time data sets will be used to analyse the data, and a multivariate linear regression machine learning technique will be used to train the machine. Using factors like the number of days, the destination city, and the number of travellers, to determine the most accurate budget for the planned trip. The proposed project uses multiple models to predict the budget based on food, travel and stay expenses. This approach works even on large data set efficiently. Also, this project can be added as an additional feature to already existing platforms such as Trip Advisor, Make My Trip, Goibibo, Airbnb, Agoda etc…