Although scikit-learn does implement most ensemble methods that we cover in this book, stacking is not one of them. In this section, we will implement custom stacking solutions for both regression and classification problems.
Python implementation
Stacking for regression
Here, we will try to create a stacking ensemble for the diabetes regression dataset. The ensemble will consist of a 5-neighbor k-Nearest Neighbors (k-NN), a decision tree limited to a max depth of four, and a ridge regression (a regularized form of least squares regression). The meta-learner will be a simple Ordinary Least Squares (OLS) linear regression.
First, we have to import the required libraries and data. Scikit-learn provides a convenient method to...