Modelling buying demand in the tourism industry based on machine training methods

Abstract

The business processes of companies in the tourism industry lend themselves well to formalization and, consequently, computer automation. This study focuses on the process of creating a demand forecast model for a travel agent based on data mining algorithms. The program code was developed in the Anaconda development environment, which allows to process the initial data and to give the prediction results for two indicators of MAE and program accuracy. The program code is designed to improve the performance of the entire system by selecting the correct functions.