Why do I get different values with pipline and without pipline in sklearn in python

Question

I am using recursive feature elimination with cross-validation (rfecv) with GridSearchCV with RandomForest classifier as follows using

Answer 1

In with pipeline case,

Feature selection (RFECV) is carried out with base model (RandomForestClassifier(random_state = 42, class_weight="balanced")) before applying the grid_searchCV on final estimator.

In without pipeline case,

For each combination of hyperparameter, the corresponding estimator is used for feature selection (RFECV). Hence, it would be time consuming.