Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/studio/evaluate-model-performance Finding TP is easy. It basically means the value where Predicted and True value is 1 and that is 11 in this case.
False Negative means where true value was 1 but predicted value was 0 and that is 1033 in this case The confusion matrix shows cases where both the predicted and actual values were 1 (known as true positives) at the top left, and cases where both the predicted and the actual values were 0 (true negatives) at the bottom right. The other cells show cases where the predicted and actual values differ (false positives and false negatives).
https://docs.microsoft.com/en-us/learn/modules/create-classification-model-azure-machine-learning-designer/evaluate-model

Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/QnAMaker/Overview/overview

Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/studio/interpret-model-results