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From: A federated learning–driven data fusion strategy for the hardenability prediction of gear steel
Figure 3. Model architecture and model prediction results. (A) MRAN-J9 architecture; (B) Model prediction results from multiple machine learning models across four clients. The blue five-pointed star indicates the lowest RMSE result. GELU: Gaussian error linear unit; ECA: efficient channel attention; R2: the coefficient of determination; RMSE: root mean square error; KNN: K-nearest neighbors regressor; LR: linear regression; RR: ridge regression; SVM: support vector machine regressor; GBDT: gradient boosting decision tree; XGB: extreme gradient boosting; RF: random forest; LGBM: light gradient boosting machine.
