22-Mar-2024, 14:09:33
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Traditional ML algorithm Performance
Dataset Size = 922
c term coefficient = 0.024832406631189047
bv term coefficient = 4.691738892379612
ang term coefficient = 0.08992101212804006
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Training set
Set size = 639
R2 = 0.928
MAE = 0.129
RMSE = 0.164
Mean Bias Error = -0.000
Mean Absolute Percentage Error = 0.045
Error Standard Deviation = 0.164
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Validation set
Set size = 213
R2 = 0.928
MAE = 0.128
RMSE = 0.157
Mean Bias Error = 0.017
Mean Absolute Percentage Error = 0.045
Error Standard Deviation = 0.157
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Test set
Set size = 213
R2 = 0.286
MAE = 0.239
RMSE = 0.307
Mean Bias Error = -0.087
Mean Absolute Percentage Error = 0.233
Error Standard Deviation = 0.294
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OUTLIERS (TEST SET)
01) 21.vasp    Error: 0.949 eV    (index=20)
02) 29.vasp    Error: 0.949 eV    (index=28)
03) 42.vasp    Error: 0.949 eV    (index=41)
04) 50.vasp    Error: 0.949 eV    (index=49)
