• R.Geethamani
• B.Karthika

House rent prediction is crucial for a common type of person because the rent of a property rises every year. Some people desire a home with a low rent cost and useful room, thus our article provides useful information about rental costs for needed customers. Hence, a methodical approach to predicting future home rentals is necessary for our demographic. The buyer who rents the home for their specific requirements is aware of the ideal rental period. Numerous factors, including location, area, square footage, rent, and house size, affect a house's rent. This research explores and implements several regression methodologies, such as linear regression, random forest regression, gradient boosting regression and XG boost regression algorithms in machine learning are used to predict the rental value of a residence.

House Rent, Linear regression, Random forest, XG boost regression, Gradient boosting regression.

"HOUSE RENT PREDICTION USING MACHINE LEARNING ALGORITHMS – A METHODICAL REVIEW", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 3, page no.112-116, March-2023, Available :http://www.jetir.org/papers/JETIRFV06022.pdf

"HOUSE RENT PREDICTION USING MACHINE LEARNING ALGORITHMS – A METHODICAL REVIEW", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 3, page no. pp112-116, March-2023, Available at : http://www.jetir.org/papers/JETIRFV06022.pdf