Question

In ensemble learning, you aggregate the predictions for weak learners, so that an ensemble of these models will give a better prediction than prediction of individual models. Which of the following statements is / are true for weak learners used in ensemble model? 1. They don’t usually overfit. 2. They have high bias, so they cannot solve complex learning problems 3. They usually overfit. A) 1 and 2 B) 1 and 3 C) 2 and 3 D) Only 1

Answer 1

The right answer is option A) 1 and 2

Both the statement are true for weak learners used in ensemble model, in ensemble learning, you aggregate the predictions for weak learners, so that an ensemble of these models will give a better prediction than prediction of individual models.

1. They don’t usually overfit. 2. They have high bias, so they cannot solve complex learning problems