Diagnosing Bias vs. Variance
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Diagnosing Bias vs. Variance
In this section we examine the relationship between the degree of the polynomial d and the underfitting or overfitting of our hypothesis.
- We need to distinguish whether bias or variance is the problem contributing to bad predictions.
- High bias is underfitting and high variance is overfitting. Ideally, we need to find a golden mean between these two.
The training error will tend to decrease as we increase the degree d of the polynomial.
At the same time, the cross validation error will tend to decrease as we increase d up to a point, and then it will increase as d is increased, forming a convex curve.
High bias (underfitting): both
High variance (overfitting):
The is summarized in the figure below:
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