Research Article
A Novel Stacking Heterogeneous Ensemble Model with Hybrid Wrapper-Based Feature Selection for Reservoir Productivity Predictions
Algorithm 1.
Algorithm 1: Proposed reservoir productivity forecast model.
(i) | Require: | (ii) | Training dataset1 , = 1, …, , where are the initial features and is the size of the training set; | (iii) | Training dataset2 , = 1, …, , where are the main features and is the size of the training set; | (iv) | Base-regressors , , …, , where is the number of base-regressors; | (v) | Ensure: | (vi) | Stacking heterogeneous ensemble regressor ; | (1) | for do | (2) | Train base-regressor on ; | (3) | end for | (4) | for each do | (5) | Construct new dataset of predictions, where ; Train a meta-regressor on . | (6) | end for | (7) | for eachdo | (8) | Train base-regressor on ; | (9) | end for | (10) | for eachdo | (11) | Construct new dataset of predictions, where ; Train a meta-regressor on . | (12) | end for | (13) | for each do | (14) | Construct new dataset of predictions, where ; Train a meta-regressor on . | (15) | end for | (16) | return; |
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