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Page 8 of 15 Gao et al. J Mater Inf 2023;3:6 https://dx.doi.org/10.20517/jmi.2023.03
Figure 3. Pearson’s correlation coefficients between characteristic variables and alloy properties. EL: elongation; UTS: ultimate tensile
strength; YS: yield strength.
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Figure 4. (A) R score and (B) MAE value of different models on 90% training set and 10% testing set. MAE: mean absolute error.
Figure 5. Performance of the MLPReg model predicted (A)UTS; (B)YS; and (C)EL on the training set and the testing set. EL: elongation;
UTS: ultimate tensile strength; YS: yield strength.
dropped dramatically with the increased size due to the overfitting. Moreover, compared with the RFReg
model, the MLPReg has a higher score overall. Therefore, the MLPReg model was selected as the optimal
model to construct the quantitative relation of “composition-process-properties” in SLMed Al-Si-(Mg)
alloy.
