Mean Squared Error1

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  MSE (Mean Squared Error) Information MSE (Mean Squared Error) is a commonly used metric to evaluate the performance of a machine learning model. It measures the average squared difference between the predicted values and the actual values. To calculate the MSE, you take the sum of the squared differences between the predicted and actual values, and then divide by the number of data points. The formula for MSE is: (1/n) .. Zettelkasten/Terminology Information 2023. 2. 22.