22-Mar-2024, 14:09:30
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Traditional ML algorithm Performance
Dataset Size = 922
c term coefficient = 0.02461279091576444
bv term coefficient = 4.588375771654248
ang term coefficient = 0.09235491430753329
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Training set
Set size = 639
R2 = 0.923
MAE = 0.129
RMSE = 0.164
Mean Bias Error = 0.000
Mean Absolute Percentage Error = 0.044
Error Standard Deviation = 0.164
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Validation set
Set size = 213
R2 = 0.934
MAE = 0.131
RMSE = 0.175
Mean Bias Error = -0.003
Mean Absolute Percentage Error = 0.047
Error Standard Deviation = 0.175
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Test set
Set size = 213
R2 = 0.307
MAE = 0.241
RMSE = 0.302
Mean Bias Error = -0.098
Mean Absolute Percentage Error = 0.237
Error Standard Deviation = 0.286
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OUTLIERS (TEST SET)
01) 21.vasp    Error: 0.895 eV    (index=20)
02) 29.vasp    Error: 0.895 eV    (index=28)
03) 42.vasp    Error: 0.895 eV    (index=41)
04) 50.vasp    Error: 0.895 eV    (index=49)
