18-Mar-2024, 15:50:05
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Traditional ML algorithm Performance
Dataset Size = 400
c term coefficient = 0.026045242904956672
bv term coefficient = 4.389814538606431
ang term coefficient = 0.09277140102897831
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Training set
Set size = 240
R2 = 0.929
MAE = 0.132
RMSE = 0.168
Mean Bias Error = -0.000
Mean Absolute Percentage Error = 0.046
Error Standard Deviation = 0.168
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Validation set
Set size = 80
R2 = 0.938
MAE = 0.119
RMSE = 0.157
Mean Bias Error = 0.012
Mean Absolute Percentage Error = 0.044
Error Standard Deviation = 0.157
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Test set
Set size = 80
R2 = 0.909
MAE = 0.152
RMSE = 0.200
Mean Bias Error = -0.051
Mean Absolute Percentage Error = 0.051
Error Standard Deviation = 0.194
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OUTLIERS (TEST SET)
01) 126.vasp    Error: -0.639 eV    (index=14)
02) 265.vasp    Error: -0.600 eV    (index=43)
