18-Mar-2024, 15:37:03
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Traditional ML algorithm Performance
Dataset Size = 1065
c term coefficient = 0.0268364685783091
bv term coefficient = 4.385147933479994
ang term coefficient = 0.09325697564028501
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Training set
Set size = 639
R2 = 0.934
MAE = 0.127
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 = 213
R2 = 0.929
MAE = 0.126
RMSE = 0.156
Mean Bias Error = 0.013
Mean Absolute Percentage Error = 0.044
Error Standard Deviation = 0.155
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Test set
Set size = 213
R2 = 0.913
MAE = 0.133
RMSE = 0.173
Mean Bias Error = -0.015
Mean Absolute Percentage Error = 0.045
Error Standard Deviation = 0.172
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OUTLIERS (TEST SET)
01) 126.vasp    Error: -0.639 eV    (index=14)
02) 265.vasp    Error: -0.603 eV    (index=43)
03) 712.vasp    Error: -0.574 eV    (index=149)
