Machine Learning-Based Home Price Prediction

Abstract

21st Century population management is an excellent challenge for all of us. The current population of India in 2022 is 1,406,631,776, a 0.95% increase from 2021. It is obvious that people need more houses in this situation in order to meet their needs. Consequently, it creates a burden for the real estate industry. It is nearly impossible for a general person to find the estimated price for the house that he wants, as well as to compare the prices of different houses. It is common for the general public to have no knowledge of the real estate market. For this reason, they are forced to pay a lot for information about the house they are interested in. As a result, there is such a high overall house price because of the fact that a middleman or a group of middlemen take an extra fee for this information from the buyer. To overcome this problem for the general public, we propose a supervised machine learning algorithm that will predict estimated home prices in Bengaluru, the capital and the largest city of the Indian state of Karnataka, based on the buyer's preferences such as location, total_sqft, bath, and bhk. The algorithm will determine the best fit.