MUMBAI, India, June 26 -- Intellectual Property India has published a patent application (202621051302 A) filed by Moresh Madhukar Mukhedkar; Sakshi Yadav; Adesh Mendre; Yash Mahajan; Dr. Shweta Koparde; and Dr Vivek Patil on April 22, 2026, for House Price Prediction.
Inventors include Moresh Madhukar Mukhedkar; Sakshi Yadav; Adesh Mendre; Yash Mahajan; Dr. Shweta Koparde; and Dr Vivek Patil.
The application for the patent was published on June 19, 2026, under issue no. 25/2026.
Abstract: House price prediction is one of the most significant applications of Machine Learning in the real estate industry. Accurate estimation of property prices helps buyers, sellers, investors, banks, and real estate agencies make informed decisions. Traditional house valuation methods are often manual, subjective, and inconsistent. With the advancement of data analytics and artificial intelligence, predictive models can now analyze large volumes of housing data and provide accurate price estimations. This project presents the design and implementation of a Machine Learning-based system for predicting house prices. Various regression algorithms such as Linear Regression and Random Forest Regressor are implemented and compared. The system performs data preprocessing, feature engineering, model training, and evaluation using performance metrics such as Mean Absolute Error (MAE), Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and R² Score.
Disclaimer: Curated by HT Syndication.
