18-Mar-2024, 16:29:25
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Traditional ML algorithm Performance
Dataset Size = 800
c term coefficient = 0.023871066358230265
bv term coefficient = 4.720610620782556
ang term coefficient = 0.09268373572965777
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Training set
Set size = 480
R2 = 0.928
MAE = 0.129
RMSE = 0.163
Mean Bias Error = -0.000
Mean Absolute Percentage Error = 0.045
Error Standard Deviation = 0.163
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Validation set
Set size = 160
R2 = 0.933
MAE = 0.132
RMSE = 0.161
Mean Bias Error = 0.005
Mean Absolute Percentage Error = 0.048
Error Standard Deviation = 0.161
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Test set
Set size = 160
R2 = 0.929
MAE = 0.135
RMSE = 0.182
Mean Bias Error = -0.002
Mean Absolute Percentage Error = 0.049
Error Standard Deviation = 0.182
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OUTLIERS (TEST SET)
01) 23.vasp    Error: -0.564 eV    (index=44)
02) 46.vasp    Error: -0.673 eV    (index=86)
03) 625.vasp    Error: -0.791 eV    (index=123)
