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MSE stands for Mean Squared Error. It is a measure of the performance of an estimate or prediction, equal to the mean squared difference between the observed values and the estimated / predicted values.

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Mean squared error (MSE) vs Least squares error (LSE)

LSE is a deterministic metric, but MSE is a stochastic (statistical) metric. to choose a proper metric you should know your question. if problem is stated in statistical expression, you should use MSE, … But in when you know statistics of output, weighting with probability metrics will give better results, which is MSE. …
mehdi morshedi's user avatar