Machine Learning 面接の質問と回答
Question: How does the term 'bias' and 'variance' relate to model error in machine learning?Answer: Bias refers to the error introduced by approximating a real-world problem with a simplified model. Variance is the amount by which the model's prediction would change if it were estimated using a different training dataset. The bias-variance tradeoff aims to balance these two sources of error. |
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