Matthews

Matthews, often referring to the Matthews Correlation Coefficient (MCC), is a statistical measure used to evaluate the quality of binary classification tests. It considers true positives, true negatives, false positives, and false negatives, providing a single score that reflects how well a model predicts both categories. Unlike accuracy, MCC accounts for imbalanced datasets and offers a more balanced view of performance. The score ranges from -1 to +1, where +1 indicates perfect prediction, 0 suggests random guessing, and -1 signifies complete disagreement between predictions and actual outcomes.