May 2020
Intermediate to advanced
530 pages
17h 8m
English
Mean squared error (MSE) is a widely used metric for regression algorithms to estimate their quality. It is an average squared difference between the predictions and ground truth values. This is given by the following equation:

Here,
is the number of predictions and ground truth items,
is the ground truth value for the ith item, and is the prediction value for the ith item.
MSE is often used as ...
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