The proportion of true positive results in all positive predictions made by the classifier.
$$
\text{Precision} = \frac{\text{True Positives}}{\text{True Positives} + \text{False Positives}}
$$
Measures the accuracy of positive predictions.
Useful when the cost of false positives is high (e.g., spam detection).
Parameters and Hyperparameters