Complexity, bias and variance
In the video, you saw how the complexity of a model labeled \(\hat{f}\) influences the bias and variance terms of its generalization error.
Which of the following correctly describes the relationship between \(\hat{f}\)'s complexity and \(\hat{f}\)'s bias and variance terms?
This exercise is part of the course
Machine Learning with Tree-Based Models in Python
Hands-on interactive exercise
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