18-Mar-2024, 15:50:05
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Traditional ML algorithm Performance
Dataset Size = 400
c term coefficient = 0.026176250570846972
bv term coefficient = 4.3866584869093606
ang term coefficient = 0.09512022969613752
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Training set
Set size = 240
R2 = 0.938
MAE = 0.126
RMSE = 0.164
Mean Bias Error = -0.000
Mean Absolute Percentage Error = 0.046
Error Standard Deviation = 0.164
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Validation set
Set size = 80
R2 = 0.902
MAE = 0.136
RMSE = 0.169
Mean Bias Error = -0.006
Mean Absolute Percentage Error = 0.047
Error Standard Deviation = 0.169
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Test set
Set size = 80
R2 = 0.908
MAE = 0.152
RMSE = 0.202
Mean Bias Error = -0.056
Mean Absolute Percentage Error = 0.051
Error Standard Deviation = 0.194
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OUTLIERS (TEST SET)
01) 126.vasp    Error: -0.648 eV    (index=14)
02) 265.vasp    Error: -0.610 eV    (index=43)
