top1% recall

"Top1% recall" refers to a performance metric used in machine learning and information retrieval tasks, which measures the percentage of relevant items that are retrieved by a system out of all relevant items available. In other words, it indicates how well a system can retrieve all the relevant items from a given dataset.

For example, if there are 100 relevant items in a dataset and a system retrieves 99 of them, then the top1% recall for that system would be 99%. This metric is often used in search engines, recommender systems, and other applications where retrieving relevant items is important.

Achieving a high top1% recall is desirable as it indicates that the system is able to retrieve most of the relevant items, which can lead to better user satisfaction and improved performance.