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Describe the bias-variance tradeoff in the context of machine learning and provide a practical example of how this tradeoff can be observed in a model's performance?
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General
Explain the fundamental relationship between bias and variance clearly, then provide concrete examples like decision tree depth adjustment or regularization strength in regression models to illustrate the tradeoff.
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