18-Mar-2024, 15:37:03
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Traditional ML algorithm Performance
Dataset Size = 1065
c term coefficient = 0.024832406631189047
bv term coefficient = 4.691738892379612
ang term coefficient = 0.08992101212804006
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Training set
Set size = 639
R2 = 0.928
MAE = 0.129
RMSE = 0.164
Mean Bias Error = -0.000
Mean Absolute Percentage Error = 0.045
Error Standard Deviation = 0.164
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Validation set
Set size = 213
R2 = 0.928
MAE = 0.128
RMSE = 0.157
Mean Bias Error = 0.017
Mean Absolute Percentage Error = 0.045
Error Standard Deviation = 0.157
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Test set
Set size = 213
R2 = 0.933
MAE = 0.132
RMSE = 0.176
Mean Bias Error = 0.001
Mean Absolute Percentage Error = 0.048
Error Standard Deviation = 0.176
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OUTLIERS (TEST SET)
01) 23.vasp    Error: -0.556 eV    (index=44)
02) 46.vasp    Error: -0.676 eV    (index=86)
03) 625.vasp    Error: -0.791 eV    (index=123)
