22-Mar-2024, 14:09:30
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Traditional ML algorithm Performance
Dataset Size = 922
c term coefficient = 0.02418853387497581
bv term coefficient = 4.523739228163353
ang term coefficient = 0.09957727613815975
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Training set
Set size = 639
R2 = 0.928
MAE = 0.130
RMSE = 0.167
Mean Bias Error = -0.000
Mean Absolute Percentage Error = 0.045
Error Standard Deviation = 0.167
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Validation set
Set size = 213
R2 = 0.923
MAE = 0.130
RMSE = 0.166
Mean Bias Error = 0.004
Mean Absolute Percentage Error = 0.045
Error Standard Deviation = 0.166
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Test set
Set size = 213
R2 = 0.340
MAE = 0.239
RMSE = 0.295
Mean Bias Error = -0.096
Mean Absolute Percentage Error = 0.236
Error Standard Deviation = 0.279
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OUTLIERS (TEST SET)
01) 21.vasp    Error: 0.859 eV    (index=20)
02) 29.vasp    Error: 0.859 eV    (index=28)
03) 42.vasp    Error: 0.859 eV    (index=41)
04) 50.vasp    Error: 0.859 eV    (index=49)
