19-Mar-2024, 11:02:31
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Traditional ML algorithm Performance
Dataset Size = 1000
c term coefficient = 0.026530613029384868
bv term coefficient = 4.39422525420864
ang term coefficient = 0.09363832695796397
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Training set
Set size = 600
R2 = 0.931
MAE = 0.127
RMSE = 0.160
Mean Bias Error = 0.000
Mean Absolute Percentage Error = 0.044
Error Standard Deviation = 0.160
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Validation set
Set size = 200
R2 = 0.911
MAE = 0.133
RMSE = 0.174
Mean Bias Error = -0.020
Mean Absolute Percentage Error = 0.045
Error Standard Deviation = 0.172
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Test set
Set size = 200
R2 = 0.930
MAE = 0.131
RMSE = 0.178
Mean Bias Error = -0.009
Mean Absolute Percentage Error = 0.047
Error Standard Deviation = 0.178
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OUTLIERS (TEST SET)
01) 23.vasp    Error: -0.573 eV    (index=44)
02) 46.vasp    Error: -0.681 eV    (index=86)
03) 625.vasp    Error: -0.804 eV    (index=123)
