Suppose I'm training a linear regression model using k-fold cross-validation. I'm training K times each time with a different training and test data set. So each time I train, I get different parameters (feature coefficients in the linear regression case). So I will have K parameters at the end of cross-validation. How do I arrive at the final parameters for my model?
If I'm using it to tune hyperparameters as well, do I have to do another cross-validation after fixing the parameters of my model?