Using machine learning to enrich building databases : Methods for tailored energy retrofits
Building databases are important assets when estimating and planning for national energy savings fromenergy retrofitting. However, databases often lack information on building characteristics needed to determine the feasibility of specific energy conservation measures. In this paper, machine learning methods are used to enrich the Swedish database of Energy Performance Certificates with building c
