October 2017
Beginner to intermediate
270 pages
7h
English
Content preview from Machine Learning for Developers
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Mean squared error
The mean squared error (MSE) is a risk metric equal to the expected value of the squared (quadratic) error loss.
If ŷi is the predicted value of the ith sample and yi is the corresponding true value, then the MSE estimated over n samples is defined as follows:
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