Recommender Systems
Machine Learning
The proportion of actual positive cases that were correctly identified. Measures a model's ability to find all relevant cases within a dataset.
Detailed Explanation
Recall, also known as sensitivity, measures the proportion of true positive cases correctly identified by a machine learning model. It indicates how effectively the model detects all relevant instances in the dataset, which is critical in applications like disease screening or fraud detection. High recall minimizes false negatives, ensuring fewer actual positives are missed.
Use Cases
- •Use case: A cancer screening system prioritizes high recall to ensure all potential positive cases are identified for further testing.
Related Terms
Other terms in the Machine Learning category