International Journal Of Imaging

Abstract

MACHINE LEARNING MODELS FOR REAL ESTATE PRICE FORECASTING

Author: A.Nishanth, Md. Ghouse , Hemanth , Dr. N. Krishnaiah

Abstract:

In the ever-evolving landscape of real estate, house prices play a pivotal role in shaping economic stability and individual decision-making. The valuation process often encounters numerous challenges, necessitating a data- driven approach to ensure accuracy and reliability. To address these complexities, our model integrates meticulous feature engineering, which involves advanced data cleansing, transformation, and feature selection. By leveraging sophisticated machine learning techniques, we aim to capture the underlying trends influencing property prices. The optimization phase incorporates hyperparameter tuning and cross-validation, ensuring that our predictive framework effectively generalizes across diverse datasets. This comprehensive methodology allows us to extract meaningful insights and refine valuation dynamics for more informed decision-making. Our approach is anchored in the application of supervised learning algorithms, such as linear regression and K-fold c