22-Mar-2024, 14:09:37
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Traditional ML algorithm Performance
Dataset Size = 922
c term coefficient = 0.02450323883558512
bv term coefficient = 4.6075188052689935
ang term coefficient = 0.09717451533356447
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Training set
Set size = 639
R2 = 0.931
MAE = 0.130
RMSE = 0.167
Mean Bias Error = -0.000
Mean Absolute Percentage Error = 0.046
Error Standard Deviation = 0.167
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Validation set
Set size = 213
R2 = 0.924
MAE = 0.131
RMSE = 0.165
Mean Bias Error = 0.010
Mean Absolute Percentage Error = 0.045
Error Standard Deviation = 0.165
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Test set
Set size = 213
R2 = 0.322
MAE = 0.237
RMSE = 0.299
Mean Bias Error = -0.087
Mean Absolute Percentage Error = 0.233
Error Standard Deviation = 0.285
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OUTLIERS (TEST SET)
01) 21.vasp    Error: 0.904 eV    (index=20)
02) 29.vasp    Error: 0.904 eV    (index=28)
03) 42.vasp    Error: 0.904 eV    (index=41)
04) 50.vasp    Error: 0.904 eV    (index=49)
