Hands-On Ensemble Learning with Python

Creating a stacking regressor class for scikit-learn

We can utilize the preceding code in order to create a reusable class that orchestrates the ensemble's training and prediction. All scikit-learn classifiers use the standard fit(x, y) and predict(x) methods, in order to train and predict respectively. First, we import the required libraries and declare the class and its constructor. The constructor's argument is a list of lists of scikit-learn classifiers. Each sub-list contains the level's learners. Thus, it is easy to construct a multi-level stacking ensemble. For example, a three-level ensemble can be constructed with StackingRegressor([ [l11, l12, l13],[ l21, l22], [l31] ]). We create a list of each stacking level's size (the number ...