Demographic Progress Analysis of Census Data Using Data Mining
Manan Chawda, Rutuja Rane, Srikanth Giri · 2018
The detailed statistics provided by the population census of the nation comprises of a lot of hidden patterns. These patterns when unfolded, prove to be extremely valuable in terms of assisting the decisions of the government. In this paper we aim at analysing the relationships between different attributes using data mining techniques. Examining the fields of education and health-care in detail, to predict and forecast the likely future statistics, we are trying to create a system that can aid the municipal corporations to take well-informed decisions. We have used linear regression and decision tree induction for the prediction purposes. We have implemented ARIMA models in forecasting of the data. We have also provided a detailed overview about target-based progress tracking using Monte Carlo Simulation.