An Improved Stacking Model for Equipment Spare Parts Demand Forecasting Based on Scenario Analysis

Table 4

Base and meta models of the stacking framework.

Base Learners	model_xgbr	xgb.XGBRegressor(random_state = 42)
	model_gbr	ensemble.GradientBoostingRegressor(n_estimators = 100)
	model_rf	ensemble.RandomForestRegressor(n_estimators = 20)
Meta Learner	model_lr	linear_model.LinearRegression()