A Novel Model for House Price Prediction with Machine Learning Techniques

Abstract

In this paper, we are going to use machine learning algorithms for house price prediction. House prices increases drastically every year, so we felt a need for a system that will predict house prices in the future. Due to a lack of knowledge of property assets people cannot guess the accurate price of houses. Therefore, we felt a need for a model that will predict an accurate house price. So, the main aim of our project is to predict the accurate price of the house without any loss. This survey also deals with a comparative analysis of the results of the algorithms used and the model with the highest accuracy and minimum error rate will be implemented. For the choice of prediction ways, we tend to compare and explore numerous prediction ways. We tend to utilize Linear and random forest regression as our model attributable to its liable and probabilistic methodology on model Choice. Our result exhibits that approach to the problem ought to achieve success and has the flexibility to predictions that will be compared to different house price prediction models. We have a proclivity to propose a house price prediction model to hold up a customer to estimate the proper valuation of a house.