Metrics used to evaluate the performance of regression models, such as MSE and R-squared.
Inside Regression metrics (2)
MSE — Mean squared error; average squared difference between predicted and actual values, sensitive to large errors.
R-squared — Proportion of variance in the dependent variable explained by independent variables; ranges 0 to 1.
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