Machine Learning for OpenCV 4 - Second Edition

Implementing a bagging regressor

Similarly, we can use the BaggingRegressor class to form an ensemble of regressors.

For example, we could build an ensemble of decision trees to predict housing prices from the Boston dataset of Chapter 3, First Steps in Supervised Learning.

In the following steps, you will learn how to use a bagging regressor for forming an ensemble of regressors:

1. The syntax is almost identical to setting up a bagging classifier:

In [7]: from sklearn.ensemble import BaggingRegressor...     from sklearn.tree import DecisionTreeRegressor...     bag_tree = BaggingRegressor(DecisionTreeRegressor(),...                                 max_features=0.5, n_estimators=10, ...                                 random_state=3)

2. Of course, we need to load and split the dataset as we did for the breast cancer ...