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Update ch20.md #64

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2 changes: 1 addition & 1 deletion _docs/Bias and Variance/ch20.md
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Expand Up @@ -3,7 +3,7 @@ title: 偏差和方差：误差的两大来源
permalink: /docs/ch20/
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假设你的训练集、开发集和测试集都来自相同的分布，那么每次你都应该试图去获取更多的训练数据，因为这样能单独提高性能，对吗？
假设你的训练集、开发集和测试集都服从同样的分布，那么每次你都应该试图去获取更多的训练数据，因为这样能单独提高性能，对吗？

拥有更多的数据是无害的，然而它并不总是如我们期望的那样有帮助。有时获取更多的数据可能是在浪费时间。那么，何时才应该添加数据呢？

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