House Price Prediction Using Regression Analysis


  • Aditya Joshi
  • Bhawnesh Kumar
  • Vandana Rawat
  • Mansi Srivastava
  • C.S. Yadav


House Price Prediction, Machine Learning, Regression


A house is one of the basic necessities of a family and one of the most crucial long-term purchases made. House as a property is also one of the best investments. With the high scope and demand, real estate is a highly profitable business. While purchasing a house a person looks through look for their preferred price range, and has a good idea about the kind of features they will look for in their desired house such as the number of rooms, furnishing, locality, accessibility to market, hospital, and other essential services, etc. The person then decides if the house they are considering is worth the mentioned price or not. For this, a trustable price prediction system is needed. Similarly, if a person needs to sell a house, they need a prediction system to decide the price of the house with the specifications that the house has. The prediction system can give a good idea to a seller and help them set a good price by adding all the favorable specifications of their house. A price prediction system can help both the buyer and seller by predicting the price of the house according to the features it holds. It is known that we can create such predictions through Regression in Machine Learning.




How to Cite

Aditya Joshi, Bhawnesh Kumar, Vandana Rawat, Mansi Srivastava, & C.S. Yadav. (2023). House Price Prediction Using Regression Analysis. Elementary Education Online, 20(3), 3706–3716. Retrieved from




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