We are back to participate in another Datathon hosted by Data Science Society. This time the theme is Text Analytics.
We will not be able to completely devote ourselves to the cause this time because of the exams which start in next week. But We’ll try to keep the article as simple and well detailed as possible so that it will be helpful for any new Data Science Enthusiast seeking for little helps. So Lets roll.
The National Statistical Institute of Bulgaria (NSI) conducts annually a Household Budget Survey (HBS) with an objective to get reliable and scientifically founded data on the income, expenditure, consumption and other elements of the living standard of the population as well as changes, which have occurred during the years. NSI is considering a change in the periodicity of the Household Budget Survey from yearly to once on every five years,In order to optimize the cost of carrying out the survey. Hence We are creating a model which will predict household expenditure for the next four years using linear regression model and time series. The algorithms that we will be taking help from are linear regression model & Autoregressive integrated moving average(ARIMA). So lets not waste any time and move on with it !
