19-Mar-2024, 11:02:32
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Traditional ML algorithm Performance
Dataset Size = 1000
c term coefficient = 0.024507771878080238
bv term coefficient = 4.707354951688463
ang term coefficient = 0.09137277573788789
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Training set
Set size = 600
R2 = 0.926
MAE = 0.130
RMSE = 0.165
Mean Bias Error = -0.000
Mean Absolute Percentage Error = 0.045
Error Standard Deviation = 0.165
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Validation set
Set size = 200
R2 = 0.928
MAE = 0.129
RMSE = 0.158
Mean Bias Error = 0.013
Mean Absolute Percentage Error = 0.046
Error Standard Deviation = 0.158
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Test set
Set size = 200
R2 = 0.930
MAE = 0.134
RMSE = 0.178
Mean Bias Error = -0.001
Mean Absolute Percentage Error = 0.048
Error Standard Deviation = 0.178
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OUTLIERS (TEST SET)
01) 23.vasp    Error: -0.558 eV    (index=44)
02) 46.vasp    Error: -0.671 eV    (index=86)
03) 625.vasp    Error: -0.788 eV    (index=123)
