The Rental Price Estimation Model is a machine learning-based system designed to predict the monthly rental price of properties using historical rental data. The system uses a Linear Regression algorithm to analyze the relationship between property features and rental prices.
The model considers various factors such as: State City Location Area (square feet) Number of bedrooms Number of bathrooms Amenities (parking, lift, security) Proximity to facilities (metro, school, hospital). After training on past rental listings, the system predicts rent for new properties. This helps landlords set competitive prices and tenants understand fair market value.