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What are best practices for Bias-Variance Tradeoff

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Use validation curves to see how bias and variance change with model complexity, and pick a model where both are reasonably balanced for your specific dataset size.
Real-world example A simple straight line model predicting house prices may miss important patterns, high bias, while a very complex model may fit every small detail of the training houses and fail on new houses, high variance.

Common follow-ups: What is overfitting, What is regularization, What is model complexity

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All 7 Bias-Variance Tradeoff questions