Hello,
I’m using: EmbeddingIntentClassifier for Intent Classification.
According to RASA’s documentation, EmbeddingIntentClassifier requires dense_features and/or sparse_features.
In my NLU pipeline, I have CountVectorsFeaturizer and RegexFeaturizer and they both creates sparse_features.
I want to know which one of these two components’ output: CountVectorsFeaturizer and RegexFeaturizer is used as an input for EmbeddingIntentClassifier?
What’s the role of each sparse_features?
Thank you,
