I have some doubts about cross validation and scoring a new set of observations.
Let's say I want to predict $y=b_0 + b_1x_1$ and have built a 10-fold cross-validation data set, run a regression model and calculated RMSE, MAE, CV and R-squared and let's say I am happy with results. Now I have 10 regression models (one for each fold) and if I want to score a new observation(s) I shall do:
- Produce 10 estimations for my new observation and then obtain an average estimation, or
- Average b0 and b1 to get a single model and then score my new observation
I think 1) is the right answer but I am not 100% sure.