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Table 3 Hyperparameters chosen by grid search for the base regressors (Additional file 1: Table S1)

From: Parasitic resistance as a predictor of faulty anodes in electro galvanizing: a comparison of machine learning, physical and hybrid models

Partial Least Square Regresion Max iterations = 200, N components = 2
Random Forest Regression Max depth = 8, No. estimators = 200, Min samples split = 200, Max samples = 0.5
Ada Boost Regression DecisionTreeRegressor (Max depth = 2), No. estimators = 1000, Loss = Square, Learning rate = 1