In a huge dataset for NLP it is taking very long time to classify my dataset
therefore, trying each feature extraction method separetly is time consuming and not effecient.
Is there a way that can tell me which method (TFIDF or Bag Of Words) is more likely to give the highest F1 score.
I tried test them on smaller subset (1000 records) it was fast but best method in smaller subset does not mean it is the best in complete dataset.
any other way to decide which method to use?