Estate Price Predictor for Multan City Townships Using Machine Learning

People are vigilant about buying a new house or plot where they are enthusiastic to live. They are likewise capricious in land because of inclusion of non-regularized real estate market in urban areas. Therefore, there is of an autonomous system that may predict the plot prices rationally. This paper exhibit the usage of linear, ridge, decision tree and lasso regression techniques to predict the plot prices for eight different housing societies of Multan, a major city in Pakistan. The Dataset features are chosen according to the general provisions and commonly popular demands. The system will be helpful to people to reach to their buying choice quickly with their budget limitations and financial provisions.