i'm new to cross validation approach and i want to know if the steps that i'm taking for my regression problem is correct:
- i am using nested cross validation for evaluating different algorithms(linear regression, random forest, ...) to find the winning algorithm.
- after which i will choose the winning algorithm and use Grid Search to find the best model in regard to parameter tuning. (grid.best_estimator_)
- i apply the wining model in step 2 to the whole Dataset.