I'm pretty new to spaCy and NLP in general, and I'm trying to figure out how to classify text. I've already gone through quite a few tutorials, and have figured out how to train my model, based on already classified datasets.
However, I'm struggling to understand how the text classification works, and how I can feed more data into it, to make it more accurate. For example, I want to build a custom rule based NER model, and want the classification model to to also look at those entities.
Is something like this possible, and how should I go ahead with this?