Building Energy Estimation using Machine Learning: Oslo use case

This CSV file contains building-level energy demand estimations for the city of Oslo, computed using the XGboost, a tree based Machine Learning approach. The model uses buildings' 'height', 'construction_year' and 'shared_wall_area' as input features. This dataset is an output of FAIRiCUBE Use Case 4 (UC4): Spatial and temporal assessment of neighbourhood building stock, which aims to evaluate energy consumption and material stocks in urban environments using harmonized methods across European cities.