The bias-variance trade-off
![The bias-variance trade-off](/api/v2/epubs/9781788290371/files/graphics/B04324_08_09.jpg)
Figure 8.9: The two extremes of the bias-variance tradeoff:. (left) a (complicated) model with essentially zero bias (on training data) but enormous variance, (right) a simple model with high bias but virtually no variance
In statistical learning, the bias of a model refers to the error of the model introduced by attempting to model a complicated real-life relationship with an approximation. A model with no bias will never make any errors in prediction (like the cookie-area prediction problem). A model with high bias will fail to accurately predict its dependent variable.
The variance of a model refers to how sensitive ...
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