A "True Positive" refers to a situation in which a test or diagnostic tool correctly identifies a condition or characteristic that is actually present. For example, if a medical test detects a disease in a patient who indeed has that disease, this result is classified as a true positive. It indicates that the test has successfully identified the target condition. In the context of machine learning and data analysis, a true positive occurs when a model accurately predicts a positive outcome. For instance, if a spam filter correctly identifies a spam email as spam, it is considered a true positive. This metric is crucial for evaluating the performance of predictive models.