18-Mar-2024, 15:37:03
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Traditional ML algorithm Performance
Dataset Size = 1065
c term coefficient = 0.024506533129004564
bv term coefficient = 4.554136562647024
ang term coefficient = 0.09722359022581148
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Training set
Set size = 639
R2 = 0.929
MAE = 0.128
RMSE = 0.161
Mean Bias Error = 0.000
Mean Absolute Percentage Error = 0.044
Error Standard Deviation = 0.161
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Validation set
Set size = 213
R2 = 0.924
MAE = 0.130
RMSE = 0.165
Mean Bias Error = 0.004
Mean Absolute Percentage Error = 0.045
Error Standard Deviation = 0.165
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Test set
Set size = 213
R2 = 0.934
MAE = 0.131
RMSE = 0.174
Mean Bias Error = -0.001
Mean Absolute Percentage Error = 0.047
Error Standard Deviation = 0.174
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OUTLIERS (TEST SET)
01) 23.vasp    Error: -0.569 eV    (index=44)
02) 46.vasp    Error: -0.660 eV    (index=86)
03) 625.vasp    Error: -0.784 eV    (index=123)
