I have just learned about the "bias-variance tradeoff" in machine learning, in the context of it being applied to simple regression models.

Now I am wondering: is this tradeoff a general universal principle that is applicable to every (conceivable) learning algorithm, or is it specific to particular algorithms, like regression?


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