House Price Rate Change Prediction Using Machine Learning

The real-estate market is the central tenet amongst the most focused businesses regarding pricing and it is keep fluctuating. The rate change is normal for most of the business in the real world scenario, most of the businesses will be linearly incremented not in a drastic manner, but in the real-estate sector the price change is very drastic either increment or decrement. Based on the different global and local geopolitical factors it is varying. These factors will highly influence on the price of the property. The term valuation of a property is considered as the analytical process of evaluating the net worth of the property. However, there are a wide range of factors which affect the valuation process. In prediction of the prices there are so many approaches are there based on machine learning and analytics. Majorly the regression based approaches are giving appropriate results. But in certain circumstances it is going to deviate and sudden price spike may not be reflected there. The main objective of this study is to find such rate changes along with the correlation of the global or national circumstances. The prediction or forecast the future house prices that are generated by using Linear Regression Model. Here Hyderabad region dataset is considered, which has more fluctuated rates compared to any other metropolitan cities in the past two decades.