Predicting house rent involves considering various factors such as location, size, amenities, and local market trends. Machine learning models can be employed to analyze historical rental data and make predictions. Features like neighborhood safety, proximity to public transport, and the overall condition of the property also play crucial roles. It's essential to gather relevant data and choose an appropriate model, such as linear regression or decision trees, to build an accurate prediction system. Regular updates to the model based on new data can help improve its accuracy over time.
