Abstract
Abstract: The real estate industry is seeing an increase in the use of data mining. The capacity of data mining to extricate helpful data from crude information makes it especially helpful for anticipating home estimations, essential housing characteristics, and a great many different elements. Homeowners and the real estate industry frequently feel anxious about price swings, according to research. The most useful models and important criteria for predicting home values are examined in a literature review. The adoption of Random Forest and XGBoost as the most effective models in comparison to others was confirmed by this study's findings. Additionally, our data suggest that locational and structural characteristics are significant forecasting variables for housing values. In order to identify the most effective machine learning model for conducting a study in this field and the most significant factors that influence home prices, this study will be very helpful, particularly to housing developers and academics.
Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
