Machine Learning, Data Science, Python, Statistics, Evaluation Metric.
where the model predicts positive when it shouldn’t. This can have consequences depending on the application (e.g., unnecessary treatments in a medical diagnosis). - False Negatives (FN): Points to cases where the model misses positive instances. Depending on the application, this can be critical