Julia for Data Science

Why is ensemble learning superior?

To comprehend the generalization power of ensemble learning being superior to an individual learner, Dietterich provided three reasons.

These three reasons help us understand the reason for the superiority of ensemble learning leading to a better hypothesis:

• The training information won't give adequate data to picking a single best learner. For instance, there might be numerous learners performing similarly well on the training information set. In this way, joining these learners might be a superior decision.
• The second reason is that, the search procedures of the learning algorithms may be defective. For instance, regardless of the possibility that there exists a best hypothesis, the learning algorithms may not ...