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Table 3 Mean and standard deviation of prediction performance for heat pump existence with different machine learning algorithms (Data: ISO week 10, 2020)

From: Detection of heat pumps from smart meter and open data

Algo. Models AUC Precision Recall F1
RF Model 1 0.794 (0.10) 0.733 (0.17) 0.401 (0.19) 0.691 (0.23)
RF Model 2 0.797 (0.11) 0.728 (0.17) 0.412 (0.19) 0.689 (0.23)
RF Model 3 0.822 (0.07) 0.737 (0.21) 0.449 (0.13) 0.723 (0.21)
RF Model 4 0.807 (0.07) 0.750 (0.22) 0.426 (0.12) 0.715 (0.21)
SVM Model 1 0.769 (0.11) 0.822 (0.16) 0.433 (0.19) 0.724 (0.22)
SVM Model 2 0.773 (0.11) 0.847 (0.16) 0.443 (0.18) 0.733 (0.21)
SVM Model 3 0.792 (0.10) 0.803 (0.23) 0.449 (0.15) 0.736 (0.21)
SVM Model 4 0.786 (0.11) 0.790 (0.23) 0.449 (0.15) 0.734 (0.21)
kNN Model 1 0.637 (0.06) 0.524 (0.20) 0.420 (0.13) 0.641 (0.22)
kNN Model 2 0.663 (0.12) 0.447 (0.22) 0.481 (0.26) 0.650 (0.26)
kNN Model 3 0.641 (0.09) 0.486 (0.13) 0.426 (0.18) 0.639 (0.23)
kNN Model 4 0.605 (0.11) 0.374 (0.20) 0.394 (0.19) 0.599 (0.26)
NB Model 1 0.689 (0.12) 0.267 (0.05) 0.830 (0.08) 0.413 (0.11)
NB Model 2 0.693 (0.11) 0.263 (0.05) 0.831 (0.08) 0.393 (0.12)
NB Model 3 0.701 (0.10) 0.272 (0.04) 0.821 (0.14) 0.446 (0.09)
NB Model 4 0.704 (0.11) 0.278 (0.04) 0.843 (0.13) 0.452 (0.09)
ANN Model 1 0.529 (0.09) - 0.030 (0.09) 0.456 (0.43)
ANN Model 2 0.545 (0.05) - 0.033 (0.10) 0.455 (0.43)
ANN Model 3 0.500 (0.02) - 0.000 (0.00) 0.435 (0.45)
ANN Model 4 0.536 (0.05) - 0.000 (0.00) 0.435 (0.45)
  1. *The ANN model could not predict any positive example