Fig. 4From: Enhancing neural non-intrusive load monitoring with generative adversarial networksEnergy-based F1 and balanced accuracy scores for the proposed and Kelly’s (Kelly & Knottenbelt, 2015a) Neural NILM approaches for the appliances washing machine and fridge. The approaches were only trained on the buildings with solid bars, i.e., training did not use data of building 2 for the washing machine model and building 5 for the fridge modelBack to article page