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The Confidence Score, or Classification Threshhold, indicates how sure the NLP service / machine learning model is that the respective intent was correctly assigned. The score can have a value between 0 and 1 , depending on how the neural networks work. In general, a score for each intent is calculated for each user input and the one with the highest value is returned as the result. If the confidence level falls below a predefined limit, a fallback intent is issued.

An example for the calculation of the Confidence Score at Google Dialogflow:

The following four training phrases were entered for the intent "Burger_order". Training phrases have been added:

"Burger Order",

"Order burger",

"I would like to place an order for a burger",

"I want to order a burger"

Dialogflow calculated a confidence score of 0.8 for the user input of "I would like to order a burger from you" . The NLP service Dialogflow is therefore 80% sure that the response issued from the intent "Order_a_burger" was correct. Based on this data and previously defined rules, no fallback intent is issued.

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