18-Mar-2024, 16:45:43
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Traditional ML algorithm Performance
Dataset Size = 900
c term coefficient = 0.02660476423708722
bv term coefficient = 4.19882357704898
ang term coefficient = 0.10142352910704337
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Training set
Set size = 540
R2 = 0.934
MAE = 0.127
RMSE = 0.163
Mean Bias Error = -0.000
Mean Absolute Percentage Error = 0.044
Error Standard Deviation = 0.163
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Validation set
Set size = 180
R2 = 0.916
MAE = 0.133
RMSE = 0.170
Mean Bias Error = 0.010
Mean Absolute Percentage Error = 0.046
Error Standard Deviation = 0.170
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Test set
Set size = 180
R2 = 0.905
MAE = 0.134
RMSE = 0.176
Mean Bias Error = -0.018
Mean Absolute Percentage Error = 0.044
Error Standard Deviation = 0.175
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OUTLIERS (TEST SET)
01) 126.vasp    Error: -0.647 eV    (index=14)
02) 265.vasp    Error: -0.607 eV    (index=43)
03) 712.vasp    Error: -0.566 eV    (index=149)
