According to the UiPath Communications Mining documentation, coverage is one of the four main factors that contribute to the model rating, which is a holistic measure of the model’s performance and health. Coverage assesses the proportion of the entire dataset that has informative label predictions, meaning that the predicted labels are not generic or irrelevant. Coverage is calculated as the percentage of verbatims (communication units) that have at least one informative label out of the total number of verbatims in the dataset. A high coverage indicates that the model is able to capture the main topics and intents of the communications, while a low coverage suggests that the model is missing important information or producing noisy predictions.

References:

Communications Mining - Understanding and improving model performance

Communications Mining - Model Rating

Communications Mining - It’s All in the Numbers - Assessing Model Performance with Metrics