# Using POS Tags and NERs as Features for Text Classification or Sentiment Analysis

I am trying to implement text classification and sentiment analysis from the documents.
I always use POS tags as features in the following way.

Mike is playing football

I would convert it into this format: Word_POS

Mike_Noun is_Verb playing_Verb football_Noun

I wanted to know what are the ways I can use NER as features. One of the ways I use is by taking count of NERs as Features. So my sentence would be

Mike_Noun is_Verb playing_Verb football_Noun 0 0

Where 0 is the number of ORG-organisations entities and another 0 is the number of e.g., DATE entities.

So I have 2 questions:

What are the other ways we can use POS tags and NERs as features in

1. Without deep learning?
2. With deep learning