Sure Pass Exam UiPath-SAIv1 PDF

If Label X has 80% precision at a given confidence threshold, this means that out of every 100 messages predicted to have Label X, 80 are correctly labelled, and 20 are incorrectly assigned the label. Precision measures the correctness of predictions made, so in this case, 80% of the predictions were correct, while 20% were false positives​

According to the UiPath documentation, the available options for Scoring in Document Manager, that apply only to string content type, are exact match and Levenshtein. Exact match is a scoring strategy that considers a prediction to be correct only if it exactly matches the true value. Levenshtein is a scoring strategy that measures the similarity between two strings by counting the minimum number of edits (insertions, deletions, or substitutions) required to transform one string into another. The lower the Levenshtein distance, the higher the score. These options can be configured in the Advanced tab of the Edit Field window for string fields.

References:

Document Understanding - Create and Configure Fields

Document Understanding - Training High Performing Models

The model rating is a proprietary score that assesses the overall health and performance of a model in UiPath Communications Mining. It considers four main factors: balance, underperforming labels, coverage, and all labels. The model rating is a score from 0 to 100, which equates to a rating of ‘Poor’ (0-49), ‘Average’ (50-69), ‘Good’ (70-89) or ‘Excellent’ (90-100). A model rating of 70-90 or better indicates that the model has sufficient training and performs well in all of the most important areas. A model rating of 70-90 or better also means that the model has a balanced and representative training data, a low number of labels with performance issues or warnings, a high coverage of the dataset by informative labels, and a high average precision of all labels.

References: Communications Mining - Model Rating, Communications Mining - Understanding and improving model performance