Price Prediction Using Machine Learning Approaches

The common problem for the average home buyers is that which property is the best on the market and has the right price. Home buyers have a hard time choosing and cannot make an informed decision without research. Customers make decisions based on their short-term needs or get confused about customer needs while ignoring their long-term needs. Real estate prices are part of the economy, and reasonable real estate prices are attractive to buyers and sellers. A quality property is a good personal investment. With the development of the city, hundreds of real estate transactions take place every day and real estate prices in the city vary greatly. It is difficult to predict the best real estate price, and it is one-time cost. This has also put them at a competitive disadvantage among real estate agents as they are used to calculating prices manually, which always leads to irrelevant prices. It’s also disappointing for buyers or sellers to take account of them. This research presents the application of diverse machine learning methodologies in the domain of real estate, presenting a novel framework that enhances the precision and adaptability of price prediction models for informed decision-making in the ever-evolving real estate market.