A Regression Approach to Distribution and Trend Analysis of Quarterly Foreign Tourist Arrivals in India

Abstract

International Tourism has been a very important contributor to a country's economic development. In developing countries like Argentina, Brazil, India etc., the tourism industry plays an important role in the Gross Domestic Product and Foreign Exchange Earnings. Now a days, India has been welcoming a highly impressive number of foreign tourists from all round the globe annually. This study aims at analysing the distribution and trend of foreign tourists visiting India, among the four quarters of a year, given different configurations of Gross Domestic Product and Foreign Exchange Earnings using Machine Learning and Regression Analysis. A 4 headed Machine Learning Model has been constructed and trained independently for the purpose. Finally, the results of the four individually trained sub models are collected together for Trend Anal ysis and Distribution Analysis. This final evaluation is done for the year 2012 post to Model Construction, Training, Tuning and Individual Validations of the 4 sub models. It has been found that the Distribution and Trend Analysis have been almost similar to the Original Distribution and Trends of Foreign Tourists among the four quarters of 2012. This similarity in Distribution Analysis has been shown using visualizations like Pie Chart and that in Trend Analysis has been shown using Line Plots.