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Root mean squared error (RMSE) for the best-performing linear regression models with k = [1,2, . . . 8] predictors. The best model for each k was considered the model with the lowest RMSE out of all possible models containing k predictors. Adding additional signals improves predictive performance, but with diminishing return.
