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?

Very hard Difficulty

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ML Knowledge question

ML Knowledge questions test your theoretical understanding of machine learning concepts. Showcase your grasp of algorithms, model training techniques, feature engineering, and the mathematical foundations of artificial intelligence.

Here's a Hint

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.