Abstract

Population growthprediction shows the future rate of fertility, mortality and migration of people of a country. It is very important for the population and health system. Nowadays, Machine learning concepts are most growing and popular for predicting future values. In order to predict population growth, the machine learning concept applied to build the map between year and population growth. The paper investigates the population growth of Indian government population data using time series forecasting machine learning techniques and analyzed byLinear regression, Support Vector Regression, Multilayer perceptron and Decision tree classifier. The optimum prediction method is based on the technique which gives very less error rate. The increment or degradation of instances in datasets do not affect the performance of the techniques is also analysed. The obtained result shows that the linear regression gives less error than the other classifier to predict population growth of India.