Price Prediction System

Abstract

Nowadays house prices tend to increase frequently. This is due to the demand for residential sector every year, especially in urban areas. Prediction of house prices is important, especially for property investors and property buyers. While buying a piece of house, a person may be reported prices much higher than their actual values. While selling their house, the person may be reported prices lower than their values. The current house negotiation process in the rural areas involves unauthorized officials carry out the house transactions with traditionally defined parameters that lack clarity, and hence the buyers/sellers are tricked easily. The pricing prediction system uses concepts of machine learning as well as model evaluation and validation techniques to establish a system capable to predict the price of house accurately. The system uses algorithms that consider relevant parameters which affect the suitability of a piece of house, hence ultimately affecting the price. The system is a useful tool for the lesser educated people living in the rural areas who are unaware of the legitimate pricing of house and are tricked into being informed the price much higher that it’s actual value.