Prof Axel asked if it was possible to have a case where Training data consists of both positive and negative examples as it may lead to better learning of the model.
Current chatbot has only positive examples with QA, Sessa and Eliza the three options. Negative feedback removes the training example from the file and re-trains the model
Study whether it is possible to handle negative examples of training data.
Prof Axel asked if it was possible to have a case where Training data consists of both positive and negative examples as it may lead to better learning of the model.
Current chatbot has only positive examples with QA, Sessa and Eliza the three options. Negative feedback removes the training example from the file and re-trains the model
Study whether it is possible to handle negative examples of training data.