Hands-On Ensemble Learning with Python

Improving voting

Although our results are better than linear regression, we can further improve them by removing the linear regression, thus, leaving the base learners as follows:

base_learners = [('SVR', SVR()), ('KNN', KNeighborsRegressor())]

This further improves the MSE, reducing it to 15.71. If we utilize this model as a trading strategy, we can achieve a Sharpe value of 0.21; considerably better than simple linear regression. The following table summarizes our results:

Metric	SVR-KNN	SVR-LR-KNN
MSE	15.71	16.22
Sharpe	0.21	0.22

Voting ensemble results