Table 1.

Runtime parameters for Gradient Boosting Regressor.

Model Type	Common Values	Unique Values
Gradient Boosting Regressor_A	alpha: 0.9; ccp_alpha: 0.0; criterion:friedman_mse; init: None; learning_rate: 0.2; loss: squared_error;	max depth: 4; n estimators: 10
	max_features: None; max_leaf_nodes: None; min_impurity_decrease: 0.0; min_samples_leaf: 1;
Gradient Boosting Regressor_B	min_samples_split: 2; min_weight_fraction_leaf: 0.0; n_iter_no_change: None; random_state: 42;	max depth’: 2; n estimators: 13
	subsample: 1.0; ‘tol’: 0.0001; validation_fraction: 0.1; verbose: 0; warm_start: False.