Machine Learning plays a virtual role from past years in normal speech command, product recommendation as well as in medical field also. Instead of this it provides better customer services and safer automobile system. This all of things shows that ML is trending technology in almost all fields so we are try to coined up ML in our project. Nowadays the real estate market is a standout amongst the most focused regarding pricing and keep fluctuating. People are looking to buy a new home with their budgets and by analysing market strategies. But main disadvantage of current system is to calculate a price of house without necessary prediction about future market trends and result is price increase. So the main aim of our project is to predict accurate price of house without any loss. There are many factors that have to be taken into consideration for predicting house price and try to predict efficient house pricing for customers with respect to their budget as well as also according to their priorities. So we are create a housing cost prediction model. By using Machine learning algorithms like Linear Regression, Decision Tree Regression, K-Means Regression and Random Forest Regression. This model will help people to put resources into a bequest without moving towards a broker. The result of this research provide that the Random Forest Regression gives maximum accuracy.
Random forest regression, machine learning
IRE Journals:
Anand G. Rawool , Dattatray V. Rogye , Sainath G. Rane , Dr. Vinayak A. Bharadi
"House Price Prediction Using Machine Learning" Iconic Research And Engineering Journals Volume 4 Issue 11 2021 Page 29-33
IEEE:
Anand G. Rawool , Dattatray V. Rogye , Sainath G. Rane , Dr. Vinayak A. Bharadi
"House Price Prediction Using Machine Learning" Iconic Research And Engineering Journals, 4(11)