My NLU file is large. Not too many of intents, but intents with thousands of examples. The problem is that intents with few examples are no more detected. the intent “stop” contains the example “stop”, and the intent “deny” contains the example “no”. However, typing “stop” or “no” get a confidence score in intent classification as low as 0.2 (and nlu_fallback gets activated).
How to fix this problem?
I think a partial solution is to make some examples like stop or no map directly to an intent. Something like KeywordIntentClassifier, but with the ability to specify which intents to load (and not load everything). The other alternative is to up-sample somehow the examples of the minority classes.