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Mean Squared Error and the Bias-Variance Decomposition
When the loss is mean squared error, bias and variance can be written exactly, and the expected total error splits into those two parts. For practical decisions about what to change next in a machine learning project, a qualitative understanding of bias and variance is usually enough.
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Learn After
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With mean squared error, bias and variance can be written as formulas, and the total error decomposes into those parts.