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Table 2 MAE performance of each model on the four tasks

From: A multitask GNN-based interpretable model for discovery of selective JAK inhibitors

  Methods Training set Validation set Test set
Global MTATFP 0.15 0.37 0.37
STATFP 0.21 0.40 0.40
LightGBM_MD 0.22 0.45 0.44
LightGBM_ECFP4 0.23 0.43 0.43
JAK1 MTATFP 0.19 0.37 0.39
STATFP 0.18 0.36 0.39
LightGBM_MD 0.25 0.45 0.44
LightGBM_ECFP4 0.24 0.42 0.44
JAK2 MTATFP 0.18 0.38 0.38
STATFP 0.21 0.40 0.40
LightGBM_MD 0.22 0.48 0.47
LightGBM_ECFP4 0.25 0.46 0.46
JAK3 MTATFP 0.16 0.42 0.41
STATFP 0.27 0.49 0.47
LightGBM_MD 0.24 0.49 0.48
LightGBM_ECFP4 0.26 0.48 0.45
TYK2 MTATFP 0.15 0.30 0.30
STATFP 0.19 0.34 0.35
LightGBM_MD 0.15 0.36 0.38
LightGBM_ECFP4 0.18 0.37 0.37
  1. The lower the MAE value was, the better the model performed