Table 1

The best selected hyperparameters

	Algorithm	Hyperparameters
1	Multiple linear regression	positive=False, n_jobs=2, fit_intercept=True, copy_X=True
2	Random forest regressor	n_estimators=90, min_samples_split=2, min_samples_leaf=1, max_samples 10000, max_features: sqrt, max_depth=10
3	SVM regressor	C=9.11158, loss='epsilon_insensitive', max_iter=5000
4	XGBoost regressor	subsample=1, min_child_weight=5, max_depth=6, learning_rate=0.1, colsample_bytree=0.75
5	MLP	solver= ‘sgd’, Learning_rate= ‘adaptive’, hidden_layer_sizes: (20,), alpha: 0.001, activation: logistic
6	DL	Optimizer= ‘sgd’, batch_size=16, activation= ‘relu’