18-Mar-2024, 16:02:47
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Traditional ML algorithm Performance
Dataset Size = 600
c term coefficient = 0.02714346076542518
bv term coefficient = 4.2418583739891895
ang term coefficient = 0.09236441920176909
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Training set
Set size = 360
R2 = 0.943
MAE = 0.123
RMSE = 0.155
Mean Bias Error = -0.000
Mean Absolute Percentage Error = 0.044
Error Standard Deviation = 0.155
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Validation set
Set size = 120
R2 = 0.938
MAE = 0.131
RMSE = 0.173
Mean Bias Error = -0.003
Mean Absolute Percentage Error = 0.048
Error Standard Deviation = 0.173
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Test set
Set size = 120
R2 = 0.905
MAE = 0.148
RMSE = 0.192
Mean Bias Error = -0.036
Mean Absolute Percentage Error = 0.049
Error Standard Deviation = 0.188
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OUTLIERS (TEST SET)
01) 126.vasp    Error: -0.650 eV    (index=14)
02) 265.vasp    Error: -0.613 eV    (index=43)
