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Energy Performance Forecasting in Buildings Using Machine Learning Algorithms, addresses the critical issue of energy consumption and efficiency in buildings. The primary problem it seeks to overcome is the limitation of existing approaches that provide predictions for the entire building’s energy consumption without offering insights into room-wise energy patterns. So, it seeks to overcome this drawback by employing various regression techniques to predict energy levels in each room, enabling a more detailed and understanding of energy usage within the building. This study proposes a comprehensive system for predicting energy performance in each room of a building using various machine learning algorithms, including Linear Regression, Ridge Regression, K-Nearest Neighbors (KNN) Regression, Decision Tree Regression, Random Forest Regression, and Gradient Boosting Regression. The system is …