mean squared error (mse)
Mean squared error (MSE) is a statistical measurement used to assess the average square difference between predicted values and actual values in a dataset. It quantifies the overall estimation error by squaring the differences, summing them, and dividing by the number of observations. A lower MSE indicates better accuracy of predictions.
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