📖 Mean Squared Error (MSE)
The mean squared error for regression is $\\text{MSE} = \\frac{1}{n}\\sum_{i=1}^{n}(y_i - \\hat{f}(x_i))^2$ where $\\hat{f}(x_i)$ is the prediction for the $i$th observation.
From: Intro to Statistical Learning
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