18-Mar-2024, 15:55:47
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Traditional ML algorithm Performance
Dataset Size = 500
c term coefficient = 0.02603042748661446
bv term coefficient = 4.331381192923319
ang term coefficient = 0.0938277151022051
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Training set
Set size = 300
R2 = 0.934
MAE = 0.130
RMSE = 0.165
Mean Bias Error = -0.000
Mean Absolute Percentage Error = 0.046
Error Standard Deviation = 0.165
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Validation set
Set size = 100
R2 = 0.940
MAE = 0.115
RMSE = 0.151
Mean Bias Error = -0.000
Mean Absolute Percentage Error = 0.041
Error Standard Deviation = 0.151
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Test set
Set size = 100
R2 = 0.912
MAE = 0.144
RMSE = 0.190
Mean Bias Error = -0.038
Mean Absolute Percentage Error = 0.048
Error Standard Deviation = 0.186
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OUTLIERS (TEST SET)
01) 126.vasp    Error: -0.640 eV    (index=14)
02) 265.vasp    Error: -0.600 eV    (index=43)
