Accuracy Metrics

Accuracy metrics measure how well a model's predictions match actual outcomes. In simple terms, they tell us the percentage of correct predictions out of all attempts. For example, if a model predicts correctly 90 times out of 100, its accuracy is 90%. These metrics are useful for understanding overall performance, but should be considered alongside others like precision and recall—especially in cases with imbalanced data—to get a complete picture of a model’s effectiveness.