Mean Square Error (MSE) is a metric used to measure the average of the squares of the errors, which are the differences between predicted values and actual values. It quantifies how close a predicted model is to the actual outcomes, providing a way to assess the accuracy of models, especially in numerical predictions or simulations.
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