Mastering Python for Finance - Second Edition

Bagging regressor

The BaggingRegressor class of sklearn.ensemble implements the bagging regressor. We can see how a bagging regressor works for multi-asset predictions of the percentage returns of JPM. The following code illustrates this:

In [ ]:    from sklearn.ensemble import BaggingRegressor    class BaggingRegressorModel(LinearRegressionModel):        def get_model(self):            return BaggingRegressor(n_estimators=20, random_state=0) In [ ]:    bagging = BaggingRegressorModel()    bagging.learn(df_lagged, y, start_date='2018',                   end_date='2019', lookback_period=10)

We created a class named BaggingRegressorModel that extends LinearRegressionModel, and the get_model() method is overridden to return the bagging regressor. The n_estimators parameter specifies 20