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- R² (coefficient of determination) compares the model's mean squared error to that of always predicting the target's mean. R² = 1.0 means perfect prediction, R² = 0.0 means the model performs the same as the naive mean predictor, and R² < 0 means the model is worse than the mean predictor. It does not directly measure accuracy in absolute units.