Confidence is the right answer bitches

Given answer is wrong. The calculated probability of a correct image classification is typically referred to as "confidence." Confidence represents the level of certainty or probability assigned to a specific classification prediction made by a machine learning model. It indicates the model's belief in the accuracy of its prediction. For example, if a model classifies an image as a dog with a confidence of 0.85, it means the model is 85% confident that the image is correctly classified as a dog. On the other hand, accuracy is a metric that measures the overall correctness of the model's predictions. It represents the ratio of correct predictions to the total number of predictions made by the model. Accuracy alone does not provide information about the level of confidence or certainty for individual predictions.

Confidence is the calculated probability of a correct image classification. PARKLIFE

CONFIDENCE IS THE CORRECT ANSWER ANO BA!

EXAM TOPICS ! Please update the answer!

Confidence https://learn.microsoft.com/en-us/training/modules/detect-objects-images-custom-vision/1a-what-is-object-detection

Confidence (as the documention describes)

After calculating the probability based on what I've learned and this forum, I'm confident that the right answer is Confidence.

Confidence is the right answer

confidence is the correct answer

Confidence is the correct answer

Scoring for classification includes: confusion matrix, accuracy, recall, precision, F1-score, and AUC. Therefore among the answer choices, accuracy is the correct one.

Confidence

Confidence is the right answer

Confidence

THE CORRECT ANSWER IS CONFIDENCE

Answer is Confidence. See: https://learn.microsoft.com/en-us/azure/ai-services/custom-vision-service/getting-started-build-a-classifier Note the Probability Threshold slider on the left pane of the Performance tab. This is the level of confidence that a prediction needs to have in order to be considered correct (for the purposes of calculating precision and recall).