How to improve the confidence score of the intent in Rasa NLU?

How to improve the confidence score of the intent in Rasa NLU?



I was working on Rasa NLU for intent classification, in link how shall I improve the confidence score for a given intent.



I have tried to give more training data but still the confidence score isn't increasing. Can anyone please let me know which parameters hyperparameters I can tune in order to get good confidence score.
I did tried to all possible combinations provided in this link but still there was hardly any improvement.



I did checked the suggestion provided over here, but I am looking for granular tuning of the model such that it can perform better.



Thanks.



Edit 1: Please provide a valid reason for down-voting the question.





Is your training data proprietary or can you share it? How many intents/training examples per intent? which pipeline? How similar are your intents? Do you have entities? I don't feel like you've provided enough information to get more of an answer than just: provide more training data.
– Caleb Keller
Aug 31 at 19:38





Sorry couldn't able to share the training data, Intents is around 44 and training distinct examples are around 1k per intent.
– Aman Dalmia
Sep 3 at 6:16





Sounds way over fit. As in way too many training examples per intent.
– Caleb Keller
Sep 3 at 20:23




2 Answers
2



You can use tensorflow_embedding which gives confidence score near to .9, rather than using spacy_sklearn which provides neat to .3



Depending whether spaCy provides a good language model for your language, you should either use the spaCy pipeline (as it comes with pretrained models) or the tensorflow_embedding pipeline which works with any language but requires more training examples.


tensorflow_embedding



I think that your problems might be caused by overlapping training examples. An example to clarify:


## intent:ask_bot_name
- Tell me your name
- What is your name
- name please

## intent:ask_location_name
- Tell me the name
- What's the name
- name please



So I would suggest to go through your training data and have a look whether different intents have the same or very very similar examples.



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