Chat bot is not correctly classify intent

when integrating rasa tracker with MongoDB, why chatbot is not correctly classified intent. it returns wrong utter

This is my configuration

language: "en"
- name: "tokenizer_whitespace"
- name: "ner_crf"
- name: "ner_synonyms"
- name: "intent_featurizer_count_vectors"
- name: "intent_classifier_tensorflow_embedding"

  - nlu_threshold: 0.3
    core_threshold: 0.3
    fallback_core_action_name: "action_default_fallback"
    fallback_nlu_action_name: "action_default_fallback"
    deny_suggestion_intent_name: "out_of_scope"

Hi janaka,

the tracker/database should have no effect on the classification. Try retraining your bot and testing in different situations.

Continuing the discussion from Chat bot is not correctly classify intent:

Hi @imLew

then how tracker and mongoDB effect chatbot?

is it affect to predict response by referring history of DB data

The bot responses are indeed based on the events in the history, which is stored in the tracker. However which tracker store you choose should not affect the behavior of the bot.