I have a model trained as follows.

```
random_search=RandomizedSearchCV(classifier, param_distributions=params,\
     scoring='f1',
     n_iter=100, cv=5, verbose=3, random_state=42, n_jobs=-1)
random_search.fit(X, y)
final_classifier=random_search.best_estimator_

```

My question is, do I have to train final\_classifier on entire data before putting it into production?

i.e. Should I do

```
final_clssifier.fit(X,y)

```

Or random\_search returning the model after fitting it again on entire data?
I really appreciate any help you can provide.